AML Classification Model¶

1. Loading the necessary libraries¶

2. Read the data¶

3. Exploratory Data Analysis¶

4. Feature Engineering¶

4.1 Concatenate_two_or_more_features¶

4.2 Frequency features¶

4.3 Time since features¶

4.4 Velocity features¶

4.5 Had previous fraud¶

4.6 Change in balance¶

5. Train Test Split¶

6. Model Pipeline¶

7. Model Selection¶

8. Generalization Performance¶

9. XGB feature importance¶

10. Model explainability¶

1. Loading the necessary libraries¶

In [3]:
from __future__ import print_function, division
import subprocess
import numpy as np
import pandas as pd
import datetime
import h5py
import numpy as np
from scipy import spatial
from datetime import timedelta,datetime
import matplotlib as mpl
import matplotlib.pyplot as plt
import plotly.express as px
import plotly.graph_objects as go

import sys
# !{sys.executable} -m pip install xgboost
# !{sys.executable} -m pip install catboost
import xgboost
import catboost

from sklearn.metrics import accuracy_score
from sklearn.metrics import f1_score
from sklearn.metrics import recall_score

from sklearn.model_selection import train_test_split
from sklearn.utils import resample

from sklearn.impute import SimpleImputer
from sklearn.preprocessing import OneHotEncoder, MinMaxScaler
from sklearn.pipeline import Pipeline
from sklearn.compose import ColumnTransformer
from sklearn.feature_selection import SelectFromModel

from sklearn.model_selection import TimeSeriesSplit

from xgboost import plot_importance
import shap

pd.set_option('display.max_rows', 500)
pd.set_option('display.max_columns', 500)
pd.set_option('display.width', 1000)
pd.set_option('compute.use_bottleneck',True)
pd.set_option('compute.use_numexpr',True)
pd.options.display.precision = 3
pd.set_option('display.precision', 3)
pd.set_option('display.float_format', lambda x: '%.3f' % x)

2. Read the data¶

Paysim synthetic dataset of mobile money transactions. Each step represents an hour of simulation. This dataset is scaled down 1/4 of the original dataset which is presented in the paper "PaySim: A financial mobile money simulator for fraud detection".

In [4]:
aml_data = pd.read_csv('PS_20174392719_1491204439457_log.csv', sep=',')
aml_data = aml_data.sort_values(by = ['nameDest','step']).reset_index(drop=True)
aml_data = aml_data.head(100000)
aml_data.head()
Out[4]:
step type amount nameOrig oldbalanceOrg newbalanceOrig nameDest oldbalanceDest newbalanceDest isFraud isFlaggedFraud
0 352 CASH_IN 156985.310 C1180747031 36186.000 193171.310 C1000004082 0.000 0.000 0 0
1 354 CASH_OUT 228252.330 C1978911345 953.000 0.000 C1000004082 0.000 228252.330 0 0
2 370 TRANSFER 1331742.990 C1539355936 11088.000 0.000 C1000004082 228252.330 1559995.310 0 0
3 374 CASH_OUT 363030.740 C1680720313 19486.000 0.000 C1000004082 1559995.310 1923026.060 0 0
4 379 CASH_IN 156015.830 C1185840905 55451.000 211466.830 C1000004082 1923026.060 1767010.230 0 0

  1. step - maps a unit of time in the real world. In this case 1 step is 1 hour of time. Total steps 744 (30 days simulation).

  2. type - CASH-IN, CASH-OUT, DEBIT, PAYMENT and TRANSFER.

  3. amount - amount of the transaction in local currency.

  4. nameOrig - customer who started the transaction.

  5. oldbalanceOrg - initial balance before the transaction.

  6. newbalanceOrig - new balance after the transaction.

  7. nameDest - customer who is the recipient of the transaction.

  8. oldbalanceDest - initial balance recipient before the transaction. Note that there is not information for customers that start with M (Merchants).

  9. newbalanceDest - new balance recipient after the transaction. Note that there is not information for customers that start with M (Merchants).

  10. isFraud - This is the transactions made by the fraudulent agents inside the simulation. In this specific dataset the fraudulent behavior of the agents aims to profit by taking control or customers accounts and try to empty the funds by transferring to another account and then cashing out of the system.

  11. isFlaggedFraud - The business model aims to control massive transfers from one account to another and flags illegal attempts. An illegal attempt in this dataset is an attempt to transfer more than 200.000 in a single transaction.

3. Exploratory Data Analysis¶

In [5]:
print("Data Type for each data-field\n\n")
print(aml_data.info())

Data Type for each data-field


<class 'pandas.core.frame.DataFrame'>
RangeIndex: 100000 entries, 0 to 99999
Data columns (total 11 columns):
 #   Column          Non-Null Count   Dtype  
---  ------          --------------   -----  
 0   step            100000 non-null  int64  
 1   type            100000 non-null  object 
 2   amount          100000 non-null  float64
 3   nameOrig        100000 non-null  object 
 4   oldbalanceOrg   100000 non-null  float64
 5   newbalanceOrig  100000 non-null  float64
 6   nameDest        100000 non-null  object 
 7   oldbalanceDest  100000 non-null  float64
 8   newbalanceDest  100000 non-null  float64
 9   isFraud         100000 non-null  int64  
 10  isFlaggedFraud  100000 non-null  int64  
dtypes: float64(5), int64(3), object(3)
memory usage: 8.4+ MB
None
In [6]:
print("Dataframe Shape\n\n")
print(aml_data.shape)

Dataframe Shape


(100000, 11)
In [7]:
aml_data.describe().T.style.format("{:,.0f}")
Out[7]:
  count mean std min 25% 50% 75% max
step 100,000 241 142 1 154 236 333 738
amount 100,000 261,876 675,325 4 76,767 159,810 279,180 51,990,861
oldbalanceOrg 100,000 1,226,464 3,493,829 0 0 17,310 190,918 49,585,040
newbalanceOrig 100,000 1,261,481 3,531,372 0 0 0 283,927 39,585,040
oldbalanceDest 100,000 1,620,428 3,599,760 0 146,642 564,907 1,700,329 152,338,227
newbalanceDest 100,000 1,803,755 3,889,847 0 228,118 703,375 1,898,856 152,338,227
isFraud 100,000 0 0 0 0 0 0 1
isFlaggedFraud 100,000 0 0 0 0 0 0 0
In [8]:
aml_data.describe(include = 'all').T
Out[8]:
count unique top freq mean std min 25% 50% 75% max
step 100000.000 NaN NaN NaN 241.237 142.007 1.000 154.000 236.000 333.000 738.000
type 100000 4 CASH_OUT 53245 NaN NaN NaN NaN NaN NaN NaN
amount 100000.000 NaN NaN NaN 261875.658 675325.031 3.520 76767.480 159810.295 279179.580 51990860.850
nameOrig 100000 99996 C1109429562 2 NaN NaN NaN NaN NaN NaN NaN
oldbalanceOrg 100000.000 NaN NaN NaN 1226463.903 3493828.532 0.000 0.000 17310.500 190918.383 49585040.370
newbalanceOrig 100000.000 NaN NaN NaN 1261481.336 3531371.526 0.000 0.000 0.000 283926.505 39585040.370
nameDest 100000 13388 C1023714065 97 NaN NaN NaN NaN NaN NaN NaN
oldbalanceDest 100000.000 NaN NaN NaN 1620427.585 3599759.749 0.000 146642.047 564906.975 1700329.165 152338227.260
newbalanceDest 100000.000 NaN NaN NaN 1803755.192 3889847.065 0.000 228118.378 703375.055 1898856.290 152338227.260
isFraud 100000.000 NaN NaN NaN 0.002 0.044 0.000 0.000 0.000 0.000 1.000
isFlaggedFraud 100000.000 NaN NaN NaN 0.000 0.000 0.000 0.000 0.000 0.000 0.000
In [9]:
print("Value Count : Transaction Type\n")

c = aml_data[['type']].value_counts(dropna=False)
p = aml_data[['type']].value_counts(dropna=False, normalize=True)*100
print(pd.concat([c,p], axis=1, keys=['Count', 'Percentage']).reset_index())

Value Count : Transaction Type

       type  Count  Percentage
0  CASH_OUT  53245      53.245
1   CASH_IN  33235      33.235
2  TRANSFER  12560      12.560
3     DEBIT    960       0.960
In [10]:
print("Value Count : isFraud\n\n")

c = aml_data[['isFraud']].value_counts(dropna=False)
p = aml_data[['isFraud']].value_counts(dropna=False, normalize=True)*100
print(pd.concat([c,p], axis=1, keys=['Count', 'Percentage']).reset_index())

Value Count : isFraud


   isFraud  Count  Percentage
0        0  99804      99.804
1        1    196       0.196
In [11]:
print("Value Count : isFlaggedFraud\n\n")

c = aml_data[['isFlaggedFraud']].value_counts(dropna=False)
p = aml_data[['isFlaggedFraud']].value_counts(dropna=False, normalize=True)*100
print(pd.concat([c,p], axis=1, keys=['Count', 'Percentage']).reset_index())

Value Count : isFlaggedFraud


   isFlaggedFraud   Count  Percentage
0               0  100000     100.000
In [12]:
print("Value Count : Transaction-type X isFraud\n\n")

c = aml_data[['type','isFraud']].value_counts(dropna=False)
p = aml_data[['type','isFraud']].value_counts(dropna=False, normalize=True)*100
print(pd.concat([c,p], axis=1, keys=['Count', 'Percentage']).reset_index())

Value Count : Transaction-type X isFraud


       type  isFraud  Count  Percentage
0  CASH_OUT        0  53151      53.151
1   CASH_IN        0  33235      33.235
2  TRANSFER        0  12458      12.458
3     DEBIT        0    960       0.960
4  TRANSFER        1    102       0.102
5  CASH_OUT        1     94       0.094
In [13]:
print("nameOrig with most transactions\n\n")

nameOrig_count = aml_data[['nameOrig','amount']].groupby(['nameOrig']).agg({'amount': ['count','sum']}).reset_index()

nameOrig_count.columns = [f'{i}_{j}' if j != '' else f'{i}' for i,j in nameOrig_count.columns]

nameOrig_count = nameOrig_count.sort_values(by = ['amount_count'], ascending=False).reset_index(drop=True)

nameOrig_count.head(10)

nameOrig with most transactions
Out[13]:
nameOrig amount_count amount_sum
0 C2098525306 2 97489.170
1 C1109429562 2 606420.320
2 C1760438154 2 653207.660
3 C1813517170 2 548851.290
4 C1000026057 1 223513.230
5 C356783078 1 141735.300
6 C356887809 1 425406.380
7 C356873648 1 110.460
8 C356871224 1 353816.530
9 C356857419 1 69221.930
In [14]:
print("nameDest with most transactions\n\n")

nameDest_count = aml_data[['nameDest','amount']].groupby(['nameDest']).agg({'amount': ['count','sum']}).reset_index()

nameDest_count.columns = [f'{i}_{j}' if j != '' else f'{i}' for i,j in nameDest_count.columns]

nameDest_count = nameDest_count.sort_values(by = ['amount_count'], ascending=False).reset_index(drop=True)

nameDest_count.head(10)

nameDest with most transactions
Out[14]:
nameDest amount_count amount_sum
0 C1023714065 97 42402918.400
1 C1013700132 71 27096885.990
2 C1031639563 69 26005904.310
3 C1014923261 65 18362595.130
4 C1040847151 60 48800329.850
5 C1039162432 59 35412388.740
6 C1016689071 58 18034510.180
7 C1003872245 57 12644405.270
8 C1028574311 56 21157974.370
9 C1005928818 55 44043061.020
In [15]:
print("nameDest with most transactions\n\n")

nameDest_count = aml_data[aml_data['isFraud'] == 1][['nameDest','amount']].groupby(['nameDest']).agg({'amount': ['count','sum']}).reset_index()

nameDest_count.columns = [f'{i}_{j}' if j != '' else f'{i}' for i,j in nameDest_count.columns]

nameDest_count = nameDest_count.sort_values(by = ['amount_count'], ascending=False).reset_index(drop=True)

nameDest_count.head(10)

nameDest with most transactions
Out[15]:
nameDest amount_count amount_sum
0 C104038589 2 2202769.970
1 C1013511446 2 2994972.200
2 C1028846036 1 49950.630
3 C1029613730 1 614145.310
4 C1029951793 1 221936.600
5 C103010660 1 7188425.250
6 C1030417644 1 452261.670
7 C1030933184 1 283415.100
8 C1031027989 1 1457085.280
9 C103115426 1 231161.480
In [16]:
aml_data[aml_data.nameDest == 'C104038589'].sort_values(by='step').reset_index(drop=True)
Out[16]:
step type amount nameOrig oldbalanceOrg newbalanceOrig nameDest oldbalanceDest newbalanceDest isFraud isFlaggedFraud
0 39 TRANSFER 152042.160 C1118399210 152042.160 0.000 C104038589 0.000 0.000 1 0
1 41 CASH_IN 297124.850 C1422936279 10435.000 307559.850 C104038589 0.000 0.000 0 0
2 59 CASH_OUT 2050727.810 C992917413 2050727.810 0.000 C104038589 0.000 2050727.810 1 0
3 129 CASH_IN 311671.350 C2071729942 1048.000 312719.350 C104038589 2050727.810 1739056.460 0 0
4 134 TRANSFER 459293.500 C877503262 0.000 0.000 C104038589 1739056.460 2198349.960 0 0
5 140 CASH_OUT 46821.090 C877394179 0.000 0.000 C104038589 2198349.960 2245171.050 0 0
6 146 CASH_IN 496826.440 C1914122706 866587.800 1363414.240 C104038589 2245171.050 1748344.600 0 0
7 159 CASH_OUT 203552.230 C1353972739 60271.000 0.000 C104038589 1748344.600 1951896.830 0 0
8 161 CASH_IN 6231.750 C1874765527 13047521.330 13053753.080 C104038589 1951896.830 1945665.080 0 0
9 161 CASH_OUT 191668.950 C2055457077 16050.000 0.000 C104038589 1945665.080 2137334.030 0 0
10 166 TRANSFER 662038.200 C514155596 49489.200 0.000 C104038589 2137334.030 2799372.230 0 0
11 182 CASH_IN 311677.000 C2135250871 1840306.390 2151983.390 C104038589 2799372.230 2487695.230 0 0
12 183 CASH_IN 142994.180 C1501582860 10080.090 153074.270 C104038589 2487695.230 2344701.050 0 0
13 190 CASH_OUT 40820.930 C1758389668 0.000 0.000 C104038589 2344701.050 2385521.980 0 0
14 228 CASH_OUT 305133.630 C1699312181 0.000 0.000 C104038589 2385521.980 2690655.620 0 0
15 254 CASH_OUT 219043.060 C214233519 187883.000 0.000 C104038589 2690655.620 2909698.670 0 0
16 256 TRANSFER 4417.840 C1917019347 0.000 0.000 C104038589 2909698.670 2914116.510 0 0
17 259 CASH_OUT 117729.860 C965354616 0.000 0.000 C104038589 2914116.510 3031846.370 0 0
18 284 CASH_IN 118532.170 C872297469 3188564.020 3307096.190 C104038589 3031846.370 2913314.210 0 0
19 347 CASH_IN 465159.090 C527660802 132657.000 597816.090 C104038589 2913314.210 2448155.120 0 0
20 348 CASH_OUT 36025.800 C999021425 256344.780 220318.970 C104038589 2448155.120 2484180.920 0 0
21 520 CASH_IN 34831.190 C181328714 4163684.040 4198515.230 C104038589 2484180.920 2449349.720 0 0
22 587 CASH_OUT 168424.450 C1097481164 10002.000 0.000 C104038589 2449349.720 2617774.170 0 0
In [17]:
print("Null Count\n\n")

aml_data.isnull().sum()

Null Count
Out[17]:
step              0
type              0
amount            0
nameOrig          0
oldbalanceOrg     0
newbalanceOrig    0
nameDest          0
oldbalanceDest    0
newbalanceDest    0
isFraud           0
isFlaggedFraud    0
dtype: int64

4. Feature Engineering (Building Candidate Variables)¶

4.1 Concatenate two or more features¶

In [18]:
aml_data['nameOrig_nameDest'] = aml_data['nameOrig'] + '_' + aml_data['nameDest']
aml_data['nameOrig_type'] = aml_data['nameOrig'] + '_' + aml_data['type']
aml_data['nameDest_type'] = aml_data['nameDest'] + '_' + aml_data['type']
aml_data['nameOrig_nameDest_type'] = aml_data['nameOrig'] + '_' + aml_data['nameDest'] + '_' + aml_data['type']
aml_data.head()
Out[18]:
step type amount nameOrig oldbalanceOrg newbalanceOrig nameDest oldbalanceDest newbalanceDest isFraud isFlaggedFraud nameOrig_nameDest nameOrig_type nameDest_type nameOrig_nameDest_type
0 352 CASH_IN 156985.310 C1180747031 36186.000 193171.310 C1000004082 0.000 0.000 0 0 C1180747031_C1000004082 C1180747031_CASH_IN C1000004082_CASH_IN C1180747031_C1000004082_CASH_IN
1 354 CASH_OUT 228252.330 C1978911345 953.000 0.000 C1000004082 0.000 228252.330 0 0 C1978911345_C1000004082 C1978911345_CASH_OUT C1000004082_CASH_OUT C1978911345_C1000004082_CASH_OUT
2 370 TRANSFER 1331742.990 C1539355936 11088.000 0.000 C1000004082 228252.330 1559995.310 0 0 C1539355936_C1000004082 C1539355936_TRANSFER C1000004082_TRANSFER C1539355936_C1000004082_TRANSFER
3 374 CASH_OUT 363030.740 C1680720313 19486.000 0.000 C1000004082 1559995.310 1923026.060 0 0 C1680720313_C1000004082 C1680720313_CASH_OUT C1000004082_CASH_OUT C1680720313_C1000004082_CASH_OUT
4 379 CASH_IN 156015.830 C1185840905 55451.000 211466.830 C1000004082 1923026.060 1767010.230 0 0 C1185840905_C1000004082 C1185840905_CASH_IN C1000004082_CASH_IN C1185840905_C1000004082_CASH_IN
In [19]:
aml_data['nameOrig_nameDest'] = aml_data['nameOrig'] + '_' + aml_data['nameDest']
aml_data.head()
Out[19]:
step type amount nameOrig oldbalanceOrg newbalanceOrig nameDest oldbalanceDest newbalanceDest isFraud isFlaggedFraud nameOrig_nameDest nameOrig_type nameDest_type nameOrig_nameDest_type
0 352 CASH_IN 156985.310 C1180747031 36186.000 193171.310 C1000004082 0.000 0.000 0 0 C1180747031_C1000004082 C1180747031_CASH_IN C1000004082_CASH_IN C1180747031_C1000004082_CASH_IN
1 354 CASH_OUT 228252.330 C1978911345 953.000 0.000 C1000004082 0.000 228252.330 0 0 C1978911345_C1000004082 C1978911345_CASH_OUT C1000004082_CASH_OUT C1978911345_C1000004082_CASH_OUT
2 370 TRANSFER 1331742.990 C1539355936 11088.000 0.000 C1000004082 228252.330 1559995.310 0 0 C1539355936_C1000004082 C1539355936_TRANSFER C1000004082_TRANSFER C1539355936_C1000004082_TRANSFER
3 374 CASH_OUT 363030.740 C1680720313 19486.000 0.000 C1000004082 1559995.310 1923026.060 0 0 C1680720313_C1000004082 C1680720313_CASH_OUT C1000004082_CASH_OUT C1680720313_C1000004082_CASH_OUT
4 379 CASH_IN 156015.830 C1185840905 55451.000 211466.830 C1000004082 1923026.060 1767010.230 0 0 C1185840905_C1000004082 C1185840905_CASH_IN C1000004082_CASH_IN C1185840905_C1000004082_CASH_IN
In [20]:
aml_data.shape
Out[20]:
(100000, 15)
In [21]:
aml_data['day'] = np.floor(aml_data['step'] / 24)
aml_data.tail()
Out[21]:
step type amount nameOrig oldbalanceOrg newbalanceOrig nameDest oldbalanceDest newbalanceDest isFraud isFlaggedFraud nameOrig_nameDest nameOrig_type nameDest_type nameOrig_nameDest_type day
99995 311 TRANSFER 2659639.270 C756332336 0.000 0.000 C1045241382 5455589.080 8115228.350 0 0 C756332336_C1045241382 C756332336_TRANSFER C1045241382_TRANSFER C756332336_C1045241382_TRANSFER 12.000
99996 567 CASH_IN 6379.760 C1029601855 7726901.270 7733281.030 C1045241382 8115228.350 7894633.010 0 0 C1029601855_C1045241382 C1029601855_CASH_IN C1045241382_CASH_IN C1029601855_C1045241382_CASH_IN 23.000
99997 567 CASH_IN 214215.570 C530502425 641522.070 855737.650 C1045241382 8108848.590 7894633.010 0 0 C530502425_C1045241382 C530502425_CASH_IN C1045241382_CASH_IN C530502425_C1045241382_CASH_IN 23.000
99998 686 CASH_IN 264372.690 C1214320622 14044.000 278416.690 C1045241382 7894633.010 7630260.320 0 0 C1214320622_C1045241382 C1214320622_CASH_IN C1045241382_CASH_IN C1214320622_C1045241382_CASH_IN 28.000
99999 345 CASH_OUT 270295.310 C1597777397 20121.000 0.000 C1045245797 0.000 270295.310 0 0 C1597777397_C1045245797 C1597777397_CASH_OUT C1045245797_CASH_OUT C1597777397_C1045245797_CASH_OUT 14.000

4.2 Frequency features¶

In [22]:
#np.arange(1,739)
In [23]:
def freq_amt_features(df, category_var):
    df_agg = df[['step',category_var,'amount']].groupby(['step',category_var]).agg({'amount': ['count','sum']}).reset_index()

    df_agg.columns = [f'{i}_{j}' if j != '' else f'{i}' for i,j in df_agg.columns]

    df_agg = df_agg.sort_values(by = [category_var,'step']).reset_index(drop=True)
    
    unique_step = np.arange(1,738)#np.unique(df_agg['step'])
    unique_category = np.unique(df_agg[category_var])
    
    unique_step_df = pd.DataFrame(unique_step, columns = ['step'])
    unique_category_df = pd.DataFrame(unique_category, columns = [category_var])
    
    unique_step_df['key'] = 0
    unique_category_df['key'] = 0
    cross_join_df = unique_category_df.merge(unique_step_df, on='key', how='outer').drop(columns='key')
    #print(cross_join_df.head(100))
    
    df_agg_final = cross_join_df.merge(df_agg, on=['step',category_var], how='left').fillna(0)
    
    df_agg_final[category_var + '_' + 'rolling_txn_count_1day'] = df_agg_final.groupby([category_var])['amount_count'] \
                                                .rolling(1*24, min_periods=1).sum() \
                                                .reset_index(0,drop=True)

    df_agg_final[category_var + '_' + 'rolling_txn_count_3day'] = df_agg_final.groupby([category_var])['amount_count'] \
                                                .rolling(3*24, min_periods=1).sum() \
                                                .reset_index(0,drop=True)

    df_agg_final[category_var + '_' + 'rolling_txn_count_7day'] = df_agg_final.groupby([category_var])['amount_count'] \
                                                .rolling(7*24, min_periods=1).sum() \
                                                .reset_index(0,drop=True)

    df_agg_final[category_var + '_' + 'rolling_txn_count_10day'] = df_agg_final.groupby([category_var])['amount_count'] \
                                                .rolling(10*24, min_periods=1).sum() \
                                                .reset_index(0,drop=True)

    df_agg_final[category_var + '_' + 'rolling_txn_count_14day'] = df_agg_final.groupby([category_var])['amount_count'] \
                                                .rolling(14*24, min_periods=1).sum() \
                                                .reset_index(0,drop=True)
    
    df_agg_final[category_var + '_' + 'rolling_txn_sum_1day'] = df_agg_final.groupby([category_var])['amount_sum'] \
                                                .rolling(1*24, min_periods=1).sum() \
                                                .reset_index(0,drop=True)

    df_agg_final[category_var + '_' + 'rolling_txn_sum_3day'] = df_agg_final.groupby([category_var])['amount_sum'] \
                                                .rolling(3*24, min_periods=1).sum() \
                                                .reset_index(0,drop=True)

    df_agg_final[category_var + '_' + 'rolling_txn_sum_7day'] = df_agg_final.groupby([category_var])['amount_sum'] \
                                                .rolling(7*24, min_periods=1).sum() \
                                                .reset_index(0,drop=True)

    df_agg_final[category_var + '_' + 'rolling_txn_sum_10day'] = df_agg_final.groupby([category_var])['amount_sum'] \
                                                .rolling(10*24, min_periods=1).sum() \
                                                .reset_index(0,drop=True)

    df_agg_final[category_var + '_' + 'rolling_txn_sum_14day'] = df_agg_final.groupby([category_var])['amount_sum'] \
                                                .rolling(14*24, min_periods=1).sum() \
                                                .reset_index(0,drop=True)
    
    df_agg_final[category_var + '_' + 'rolling_txn_count_mean_7day'] = df_agg_final.groupby([category_var])['amount_count'] \
                                                .rolling(7*24, min_periods=1).mean() \
                                                .reset_index(0,drop=True)

    df_agg_final[category_var + '_' + 'rolling_txn_count_mean_10day'] = df_agg_final.groupby([category_var])['amount_count'] \
                                                .rolling(10*24, min_periods=1).mean() \
                                                .reset_index(0,drop=True)

    df_agg_final[category_var + '_' + 'rolling_txn_count_mean_14day'] = df_agg_final.groupby([category_var])['amount_count'] \
                                                .rolling(14*24, min_periods=1).mean() \
                                                .reset_index(0,drop=True)    

    df_agg_final[category_var + '_' + 'rolling_txn_amount_mean_7day'] = df_agg_final.groupby([category_var])['amount_sum'] \
                                                .rolling(7*24, min_periods=1).mean() \
                                                .reset_index(0,drop=True)

    df_agg_final[category_var + '_' + 'rolling_txn_amount_mean_10day'] = df_agg_final.groupby([category_var])['amount_sum'] \
                                                .rolling(10*24, min_periods=1).mean() \
                                                .reset_index(0,drop=True)

    df_agg_final[category_var + '_' + 'rolling_txn_amount_mean_14day'] = df_agg_final.groupby([category_var])['amount_sum'] \
                                                .rolling(14*24, min_periods=1).mean() \
                                                .reset_index(0,drop=True)
    
#    df_agg_final[category_var + '_' + 'rolling_txn_amount_median_7day'] = df_agg_final.groupby([category_var])['amount_sum'] \
#                                                .rolling(7*24, min_periods=1).median() \
#                                                .reset_index(0,drop=True)
#
#    df_agg_final[category_var + '_' + 'rolling_txn_amount_median_10day'] = df_agg_final.groupby([category_var])['amount_sum'] \
#                                                .rolling(10*24, min_periods=1).median() \
#                                                .reset_index(0,drop=True)
#
#    df_agg_final[category_var + '_' + 'rolling_txn_amount_median_14day'] = df_agg_final.groupby([category_var])['amount_sum'] \
#                                                .rolling(14*24, min_periods=1).median() \
#                                                .reset_index(0,drop=True)
#    
    df_agg_final[category_var + '_' + 'rolling_txn_amount_max_7day'] = df_agg_final.groupby([category_var])['amount_sum'] \
                                                .rolling(7*24, min_periods=1).max() \
                                                .reset_index(0,drop=True)

    df_agg_final[category_var + '_' + 'rolling_txn_amount_max_10day'] = df_agg_final.groupby([category_var])['amount_sum'] \
                                                .rolling(10*24, min_periods=1).max() \
                                                .reset_index(0,drop=True)

    df_agg_final[category_var + '_' + 'rolling_txn_amount_max_14day'] = df_agg_final.groupby([category_var])['amount_sum'] \
                                                .rolling(14*24, min_periods=1).max() \
                                                .reset_index(0,drop=True)    
    
    return(df_agg_final.drop(['amount_count','amount_sum'], axis=1))
In [24]:
freq_amt_features(df = aml_data, category_var = 'nameDest').head(100)
Out[24]:
nameDest step nameDest_rolling_txn_count_1day nameDest_rolling_txn_count_3day nameDest_rolling_txn_count_7day nameDest_rolling_txn_count_10day nameDest_rolling_txn_count_14day nameDest_rolling_txn_sum_1day nameDest_rolling_txn_sum_3day nameDest_rolling_txn_sum_7day nameDest_rolling_txn_sum_10day nameDest_rolling_txn_sum_14day nameDest_rolling_txn_count_mean_7day nameDest_rolling_txn_count_mean_10day nameDest_rolling_txn_count_mean_14day nameDest_rolling_txn_amount_mean_7day nameDest_rolling_txn_amount_mean_10day nameDest_rolling_txn_amount_mean_14day nameDest_rolling_txn_amount_max_7day nameDest_rolling_txn_amount_max_10day nameDest_rolling_txn_amount_max_14day
0 C1000004082 1 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
1 C1000004082 2 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
2 C1000004082 3 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
3 C1000004082 4 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
4 C1000004082 5 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
5 C1000004082 6 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
6 C1000004082 7 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
7 C1000004082 8 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
8 C1000004082 9 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
9 C1000004082 10 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
10 C1000004082 11 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
11 C1000004082 12 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
12 C1000004082 13 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
13 C1000004082 14 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
14 C1000004082 15 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
15 C1000004082 16 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
16 C1000004082 17 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
17 C1000004082 18 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
18 C1000004082 19 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
19 C1000004082 20 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
20 C1000004082 21 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
21 C1000004082 22 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
22 C1000004082 23 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
23 C1000004082 24 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
24 C1000004082 25 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
25 C1000004082 26 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
26 C1000004082 27 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
27 C1000004082 28 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
28 C1000004082 29 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
29 C1000004082 30 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
30 C1000004082 31 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
31 C1000004082 32 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
32 C1000004082 33 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
33 C1000004082 34 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
34 C1000004082 35 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
35 C1000004082 36 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
36 C1000004082 37 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
37 C1000004082 38 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
38 C1000004082 39 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
39 C1000004082 40 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
40 C1000004082 41 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
41 C1000004082 42 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
42 C1000004082 43 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
43 C1000004082 44 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
44 C1000004082 45 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
45 C1000004082 46 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
46 C1000004082 47 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
47 C1000004082 48 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
48 C1000004082 49 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
49 C1000004082 50 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
50 C1000004082 51 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
51 C1000004082 52 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
52 C1000004082 53 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
53 C1000004082 54 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
54 C1000004082 55 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
55 C1000004082 56 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
56 C1000004082 57 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
57 C1000004082 58 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
58 C1000004082 59 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
59 C1000004082 60 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
60 C1000004082 61 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
61 C1000004082 62 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
62 C1000004082 63 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
63 C1000004082 64 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
64 C1000004082 65 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
65 C1000004082 66 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
66 C1000004082 67 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
67 C1000004082 68 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
68 C1000004082 69 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
69 C1000004082 70 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
70 C1000004082 71 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
71 C1000004082 72 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
72 C1000004082 73 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
73 C1000004082 74 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
74 C1000004082 75 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
75 C1000004082 76 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
76 C1000004082 77 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
77 C1000004082 78 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
78 C1000004082 79 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
79 C1000004082 80 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
80 C1000004082 81 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
81 C1000004082 82 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
82 C1000004082 83 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
83 C1000004082 84 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
84 C1000004082 85 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
85 C1000004082 86 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
86 C1000004082 87 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
87 C1000004082 88 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
88 C1000004082 89 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
89 C1000004082 90 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
90 C1000004082 91 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
91 C1000004082 92 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
92 C1000004082 93 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
93 C1000004082 94 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
94 C1000004082 95 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
95 C1000004082 96 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
96 C1000004082 97 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
97 C1000004082 98 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
98 C1000004082 99 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
99 C1000004082 100 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
In [25]:
#nameDest2[nameDest2.nameDest == 'C1023714065']
In [26]:
#aml_data.head()
In [27]:
nameOrig = freq_amt_features(df = aml_data, category_var = 'nameOrig')
aml_data = aml_data.merge(nameOrig, on=['nameOrig','step'], how='left')

nameDest = freq_amt_features(df = aml_data, category_var = 'nameDest')
aml_data = aml_data.merge(nameDest, on=['nameDest','step'], how='left')

nameOrig_nameDest = freq_amt_features(df = aml_data, category_var = 'nameOrig_nameDest')
aml_data = aml_data.merge(nameOrig_nameDest, on=['nameOrig_nameDest','step'], how='left')

nameOrig_type = freq_amt_features(df = aml_data, category_var = 'nameOrig_type')
aml_data = aml_data.merge(nameOrig_type, on=['nameOrig_type','step'], how='left')

nameDest_type = freq_amt_features(df = aml_data, category_var = 'nameDest_type')
aml_data = aml_data.merge(nameDest_type, on=['nameDest_type','step'], how='left')

nameOrig_nameDest_type = freq_amt_features(df = aml_data, category_var = 'nameOrig_nameDest_type')
aml_data = aml_data.merge(nameOrig_nameDest_type, on=['nameOrig_nameDest_type','step'], how='left')
In [28]:
#nameOrig_nameDest = freq_amt_features(df = aml_data, category_var = 'nameOrig_nameDest')
#aml_data = aml_data.merge(nameOrig_nameDest, on=['nameOrig_nameDest','step'], how='left')
In [29]:
aml_data.head(100)
Out[29]:
step type amount nameOrig oldbalanceOrg newbalanceOrig nameDest oldbalanceDest newbalanceDest isFraud isFlaggedFraud nameOrig_nameDest nameOrig_type nameDest_type nameOrig_nameDest_type day nameOrig_rolling_txn_count_1day nameOrig_rolling_txn_count_3day nameOrig_rolling_txn_count_7day nameOrig_rolling_txn_count_10day nameOrig_rolling_txn_count_14day nameOrig_rolling_txn_sum_1day nameOrig_rolling_txn_sum_3day nameOrig_rolling_txn_sum_7day nameOrig_rolling_txn_sum_10day nameOrig_rolling_txn_sum_14day nameOrig_rolling_txn_count_mean_7day nameOrig_rolling_txn_count_mean_10day nameOrig_rolling_txn_count_mean_14day nameOrig_rolling_txn_amount_mean_7day nameOrig_rolling_txn_amount_mean_10day nameOrig_rolling_txn_amount_mean_14day nameOrig_rolling_txn_amount_max_7day nameOrig_rolling_txn_amount_max_10day nameOrig_rolling_txn_amount_max_14day nameDest_rolling_txn_count_1day nameDest_rolling_txn_count_3day nameDest_rolling_txn_count_7day nameDest_rolling_txn_count_10day nameDest_rolling_txn_count_14day nameDest_rolling_txn_sum_1day nameDest_rolling_txn_sum_3day nameDest_rolling_txn_sum_7day nameDest_rolling_txn_sum_10day nameDest_rolling_txn_sum_14day nameDest_rolling_txn_count_mean_7day nameDest_rolling_txn_count_mean_10day nameDest_rolling_txn_count_mean_14day nameDest_rolling_txn_amount_mean_7day nameDest_rolling_txn_amount_mean_10day nameDest_rolling_txn_amount_mean_14day nameDest_rolling_txn_amount_max_7day nameDest_rolling_txn_amount_max_10day nameDest_rolling_txn_amount_max_14day nameOrig_nameDest_rolling_txn_count_1day nameOrig_nameDest_rolling_txn_count_3day nameOrig_nameDest_rolling_txn_count_7day nameOrig_nameDest_rolling_txn_count_10day nameOrig_nameDest_rolling_txn_count_14day nameOrig_nameDest_rolling_txn_sum_1day nameOrig_nameDest_rolling_txn_sum_3day nameOrig_nameDest_rolling_txn_sum_7day nameOrig_nameDest_rolling_txn_sum_10day nameOrig_nameDest_rolling_txn_sum_14day nameOrig_nameDest_rolling_txn_count_mean_7day nameOrig_nameDest_rolling_txn_count_mean_10day nameOrig_nameDest_rolling_txn_count_mean_14day nameOrig_nameDest_rolling_txn_amount_mean_7day nameOrig_nameDest_rolling_txn_amount_mean_10day nameOrig_nameDest_rolling_txn_amount_mean_14day nameOrig_nameDest_rolling_txn_amount_max_7day nameOrig_nameDest_rolling_txn_amount_max_10day nameOrig_nameDest_rolling_txn_amount_max_14day nameOrig_type_rolling_txn_count_1day nameOrig_type_rolling_txn_count_3day nameOrig_type_rolling_txn_count_7day nameOrig_type_rolling_txn_count_10day nameOrig_type_rolling_txn_count_14day nameOrig_type_rolling_txn_sum_1day nameOrig_type_rolling_txn_sum_3day nameOrig_type_rolling_txn_sum_7day nameOrig_type_rolling_txn_sum_10day nameOrig_type_rolling_txn_sum_14day nameOrig_type_rolling_txn_count_mean_7day nameOrig_type_rolling_txn_count_mean_10day nameOrig_type_rolling_txn_count_mean_14day nameOrig_type_rolling_txn_amount_mean_7day nameOrig_type_rolling_txn_amount_mean_10day nameOrig_type_rolling_txn_amount_mean_14day nameOrig_type_rolling_txn_amount_max_7day nameOrig_type_rolling_txn_amount_max_10day nameOrig_type_rolling_txn_amount_max_14day nameDest_type_rolling_txn_count_1day nameDest_type_rolling_txn_count_3day nameDest_type_rolling_txn_count_7day nameDest_type_rolling_txn_count_10day nameDest_type_rolling_txn_count_14day nameDest_type_rolling_txn_sum_1day nameDest_type_rolling_txn_sum_3day nameDest_type_rolling_txn_sum_7day nameDest_type_rolling_txn_sum_10day nameDest_type_rolling_txn_sum_14day nameDest_type_rolling_txn_count_mean_7day nameDest_type_rolling_txn_count_mean_10day nameDest_type_rolling_txn_count_mean_14day nameDest_type_rolling_txn_amount_mean_7day nameDest_type_rolling_txn_amount_mean_10day nameDest_type_rolling_txn_amount_mean_14day nameDest_type_rolling_txn_amount_max_7day nameDest_type_rolling_txn_amount_max_10day nameDest_type_rolling_txn_amount_max_14day nameOrig_nameDest_type_rolling_txn_count_1day nameOrig_nameDest_type_rolling_txn_count_3day nameOrig_nameDest_type_rolling_txn_count_7day nameOrig_nameDest_type_rolling_txn_count_10day nameOrig_nameDest_type_rolling_txn_count_14day nameOrig_nameDest_type_rolling_txn_sum_1day nameOrig_nameDest_type_rolling_txn_sum_3day nameOrig_nameDest_type_rolling_txn_sum_7day nameOrig_nameDest_type_rolling_txn_sum_10day nameOrig_nameDest_type_rolling_txn_sum_14day nameOrig_nameDest_type_rolling_txn_count_mean_7day nameOrig_nameDest_type_rolling_txn_count_mean_10day nameOrig_nameDest_type_rolling_txn_count_mean_14day nameOrig_nameDest_type_rolling_txn_amount_mean_7day nameOrig_nameDest_type_rolling_txn_amount_mean_10day nameOrig_nameDest_type_rolling_txn_amount_mean_14day nameOrig_nameDest_type_rolling_txn_amount_max_7day nameOrig_nameDest_type_rolling_txn_amount_max_10day nameOrig_nameDest_type_rolling_txn_amount_max_14day
0 352 CASH_IN 156985.310 C1180747031 36186.000 193171.310 C1000004082 0.000 0.000 0 0 C1180747031_C1000004082 C1180747031_CASH_IN C1000004082_CASH_IN C1180747031_C1000004082_CASH_IN 14.000 1.000 1.000 1.000 1.000 1.000 156985.310 156985.310 156985.310 156985.310 156985.310 0.006 0.004 0.003 934.436 654.105 467.218 156985.310 156985.310 156985.310 1.000 1.000 1.000 1.000 1.000 156985.310 156985.310 156985.310 156985.310 156985.310 0.006 0.004 0.003 934.436 654.105 467.218 156985.310 156985.310 156985.310 1.000 1.000 1.000 1.000 1.000 156985.310 156985.310 156985.310 156985.310 156985.310 0.006 0.004 0.003 934.436 654.105 467.218 156985.310 156985.310 156985.310 1.000 1.000 1.000 1.000 1.000 156985.310 156985.310 156985.310 156985.310 156985.310 0.006 0.004 0.003 934.436 654.105 467.218 156985.310 156985.310 156985.310 1.000 1.000 1.000 1.000 1.000 156985.310 156985.310 156985.310 156985.310 156985.310 0.006 0.004 0.003 934.436 654.105 467.218 156985.310 156985.310 156985.310 1.000 1.000 1.000 1.000 1.000 156985.310 156985.310 156985.310 156985.310 156985.310 0.006 0.004 0.003 934.436 654.105 467.218 156985.310 156985.310 156985.310
1 354 CASH_OUT 228252.330 C1978911345 953.000 0.000 C1000004082 0.000 228252.330 0 0 C1978911345_C1000004082 C1978911345_CASH_OUT C1000004082_CASH_OUT C1978911345_C1000004082_CASH_OUT 14.000 1.000 1.000 1.000 1.000 1.000 228252.330 228252.330 228252.330 228252.330 228252.330 0.006 0.004 0.003 1358.645 951.051 679.322 228252.330 228252.330 228252.330 2.000 2.000 2.000 2.000 2.000 385237.640 385237.640 385237.640 385237.640 385237.640 0.012 0.008 0.006 2293.081 1605.157 1146.541 228252.330 228252.330 228252.330 1.000 1.000 1.000 1.000 1.000 228252.330 228252.330 228252.330 228252.330 228252.330 0.006 0.004 0.003 1358.645 951.051 679.322 228252.330 228252.330 228252.330 1.000 1.000 1.000 1.000 1.000 228252.330 228252.330 228252.330 228252.330 228252.330 0.006 0.004 0.003 1358.645 951.051 679.322 228252.330 228252.330 228252.330 1.000 1.000 1.000 1.000 1.000 228252.330 228252.330 228252.330 228252.330 228252.330 0.006 0.004 0.003 1358.645 951.051 679.322 228252.330 228252.330 228252.330 1.000 1.000 1.000 1.000 1.000 228252.330 228252.330 228252.330 228252.330 228252.330 0.006 0.004 0.003 1358.645 951.051 679.322 228252.330 228252.330 228252.330
2 370 TRANSFER 1331742.990 C1539355936 11088.000 0.000 C1000004082 228252.330 1559995.310 0 0 C1539355936_C1000004082 C1539355936_TRANSFER C1000004082_TRANSFER C1539355936_C1000004082_TRANSFER 15.000 1.000 1.000 1.000 1.000 1.000 1331742.990 1331742.990 1331742.990 1331742.990 1331742.990 0.006 0.004 0.003 7927.042 5548.929 3963.521 1331742.990 1331742.990 1331742.990 3.000 3.000 3.000 3.000 3.000 1716980.630 1716980.630 1716980.630 1716980.630 1716980.630 0.018 0.013 0.009 10220.123 7154.086 5110.061 1331742.990 1331742.990 1331742.990 1.000 1.000 1.000 1.000 1.000 1331742.990 1331742.990 1331742.990 1331742.990 1331742.990 0.006 0.004 0.003 7927.042 5548.929 3963.521 1331742.990 1331742.990 1331742.990 1.000 1.000 1.000 1.000 1.000 1331742.990 1331742.990 1331742.990 1331742.990 1331742.990 0.006 0.004 0.003 7927.042 5548.929 3963.521 1331742.990 1331742.990 1331742.990 1.000 1.000 1.000 1.000 1.000 1331742.990 1331742.990 1331742.990 1331742.990 1331742.990 0.006 0.004 0.003 7927.042 5548.929 3963.521 1331742.990 1331742.990 1331742.990 1.000 1.000 1.000 1.000 1.000 1331742.990 1331742.990 1331742.990 1331742.990 1331742.990 0.006 0.004 0.003 7927.042 5548.929 3963.521 1331742.990 1331742.990 1331742.990
3 374 CASH_OUT 363030.740 C1680720313 19486.000 0.000 C1000004082 1559995.310 1923026.060 0 0 C1680720313_C1000004082 C1680720313_CASH_OUT C1000004082_CASH_OUT C1680720313_C1000004082_CASH_OUT 15.000 1.000 1.000 1.000 1.000 1.000 363030.740 363030.740 363030.740 363030.740 363030.740 0.006 0.004 0.003 2160.897 1512.628 1080.449 363030.740 363030.740 363030.740 4.000 4.000 4.000 4.000 4.000 2080011.370 2080011.370 2080011.370 2080011.370 2080011.370 0.024 0.017 0.012 12381.020 8666.714 6190.510 1331742.990 1331742.990 1331742.990 1.000 1.000 1.000 1.000 1.000 363030.740 363030.740 363030.740 363030.740 363030.740 0.006 0.004 0.003 2160.897 1512.628 1080.449 363030.740 363030.740 363030.740 1.000 1.000 1.000 1.000 1.000 363030.740 363030.740 363030.740 363030.740 363030.740 0.006 0.004 0.003 2160.897 1512.628 1080.449 363030.740 363030.740 363030.740 2.000 2.000 2.000 2.000 2.000 591283.070 591283.070 591283.070 591283.070 591283.070 0.012 0.008 0.006 3519.542 2463.679 1759.771 363030.740 363030.740 363030.740 1.000 1.000 1.000 1.000 1.000 363030.740 363030.740 363030.740 363030.740 363030.740 0.006 0.004 0.003 2160.897 1512.628 1080.449 363030.740 363030.740 363030.740
4 379 CASH_IN 156015.830 C1185840905 55451.000 211466.830 C1000004082 1923026.060 1767010.230 0 0 C1185840905_C1000004082 C1185840905_CASH_IN C1000004082_CASH_IN C1185840905_C1000004082_CASH_IN 15.000 1.000 1.000 1.000 1.000 1.000 156015.830 156015.830 156015.830 156015.830 156015.830 0.006 0.004 0.003 928.666 650.066 464.333 156015.830 156015.830 156015.830 3.000 5.000 5.000 5.000 5.000 1850789.560 2236027.200 2236027.200 2236027.200 2236027.200 0.030 0.021 0.015 13309.686 9316.780 6654.843 1331742.990 1331742.990 1331742.990 1.000 1.000 1.000 1.000 1.000 156015.830 156015.830 156015.830 156015.830 156015.830 0.006 0.004 0.003 928.666 650.066 464.333 156015.830 156015.830 156015.830 1.000 1.000 1.000 1.000 1.000 156015.830 156015.830 156015.830 156015.830 156015.830 0.006 0.004 0.003 928.666 650.066 464.333 156015.830 156015.830 156015.830 1.000 2.000 2.000 2.000 2.000 156015.830 313001.140 313001.140 313001.140 313001.140 0.012 0.008 0.006 1863.102 1304.171 931.551 156985.310 156985.310 156985.310 1.000 1.000 1.000 1.000 1.000 156015.830 156015.830 156015.830 156015.830 156015.830 0.006 0.004 0.003 928.666 650.066 464.333 156015.830 156015.830 156015.830
5 396 CASH_IN 23297.190 C984964842 1030993.300 1054290.490 C1000004082 1767010.230 1743713.040 0 0 C984964842_C1000004082 C984964842_CASH_IN C1000004082_CASH_IN C984964842_C1000004082_CASH_IN 16.000 1.000 1.000 1.000 1.000 1.000 23297.190 23297.190 23297.190 23297.190 23297.190 0.006 0.004 0.003 138.674 97.072 69.337 23297.190 23297.190 23297.190 3.000 6.000 6.000 6.000 6.000 542343.760 2259324.390 2259324.390 2259324.390 2259324.390 0.036 0.025 0.018 13448.359 9413.852 6724.180 1331742.990 1331742.990 1331742.990 1.000 1.000 1.000 1.000 1.000 23297.190 23297.190 23297.190 23297.190 23297.190 0.006 0.004 0.003 138.674 97.072 69.337 23297.190 23297.190 23297.190 1.000 1.000 1.000 1.000 1.000 23297.190 23297.190 23297.190 23297.190 23297.190 0.006 0.004 0.003 138.674 97.072 69.337 23297.190 23297.190 23297.190 2.000 3.000 3.000 3.000 3.000 179313.020 336298.330 336298.330 336298.330 336298.330 0.018 0.013 0.009 2001.776 1401.243 1000.888 156985.310 156985.310 156985.310 1.000 1.000 1.000 1.000 1.000 23297.190 23297.190 23297.190 23297.190 23297.190 0.006 0.004 0.003 138.674 97.072 69.337 23297.190 23297.190 23297.190
6 131 CASH_OUT 269626.350 C1456984251 62359.650 0.000 C1000004940 0.000 269626.350 0 0 C1456984251_C1000004940 C1456984251_CASH_OUT C1000004940_CASH_OUT C1456984251_C1000004940_CASH_OUT 5.000 1.000 1.000 1.000 1.000 1.000 269626.350 269626.350 269626.350 269626.350 269626.350 0.008 0.008 0.008 2058.216 2058.216 2058.216 269626.350 269626.350 269626.350 1.000 1.000 1.000 1.000 1.000 269626.350 269626.350 269626.350 269626.350 269626.350 0.008 0.008 0.008 2058.216 2058.216 2058.216 269626.350 269626.350 269626.350 1.000 1.000 1.000 1.000 1.000 269626.350 269626.350 269626.350 269626.350 269626.350 0.008 0.008 0.008 2058.216 2058.216 2058.216 269626.350 269626.350 269626.350 1.000 1.000 1.000 1.000 1.000 269626.350 269626.350 269626.350 269626.350 269626.350 0.008 0.008 0.008 2058.216 2058.216 2058.216 269626.350 269626.350 269626.350 1.000 1.000 1.000 1.000 1.000 269626.350 269626.350 269626.350 269626.350 269626.350 0.008 0.008 0.008 2058.216 2058.216 2058.216 269626.350 269626.350 269626.350 1.000 1.000 1.000 1.000 1.000 269626.350 269626.350 269626.350 269626.350 269626.350 0.008 0.008 0.008 2058.216 2058.216 2058.216 269626.350 269626.350 269626.350
7 132 CASH_IN 368907.170 C272149483 18824.000 387731.170 C1000004940 269626.350 0.000 0 0 C272149483_C1000004940 C272149483_CASH_IN C1000004940_CASH_IN C272149483_C1000004940_CASH_IN 5.000 1.000 1.000 1.000 1.000 1.000 368907.170 368907.170 368907.170 368907.170 368907.170 0.008 0.008 0.008 2794.751 2794.751 2794.751 368907.170 368907.170 368907.170 2.000 2.000 2.000 2.000 2.000 638533.520 638533.520 638533.520 638533.520 638533.520 0.015 0.015 0.015 4837.375 4837.375 4837.375 368907.170 368907.170 368907.170 1.000 1.000 1.000 1.000 1.000 368907.170 368907.170 368907.170 368907.170 368907.170 0.008 0.008 0.008 2794.751 2794.751 2794.751 368907.170 368907.170 368907.170 1.000 1.000 1.000 1.000 1.000 368907.170 368907.170 368907.170 368907.170 368907.170 0.008 0.008 0.008 2794.751 2794.751 2794.751 368907.170 368907.170 368907.170 1.000 1.000 1.000 1.000 1.000 368907.170 368907.170 368907.170 368907.170 368907.170 0.008 0.008 0.008 2794.751 2794.751 2794.751 368907.170 368907.170 368907.170 1.000 1.000 1.000 1.000 1.000 368907.170 368907.170 368907.170 368907.170 368907.170 0.008 0.008 0.008 2794.751 2794.751 2794.751 368907.170 368907.170 368907.170
8 161 CASH_OUT 181650.640 C1953934428 29979.000 0.000 C1000004940 0.000 181650.640 0 0 C1953934428_C1000004940 C1953934428_CASH_OUT C1000004940_CASH_OUT C1953934428_C1000004940_CASH_OUT 6.000 1.000 1.000 1.000 1.000 1.000 181650.640 181650.640 181650.640 181650.640 181650.640 0.006 0.006 0.006 1128.265 1128.265 1128.265 181650.640 181650.640 181650.640 1.000 3.000 3.000 3.000 3.000 181650.640 820184.160 820184.160 820184.160 820184.160 0.019 0.019 0.019 5094.312 5094.312 5094.312 368907.170 368907.170 368907.170 1.000 1.000 1.000 1.000 1.000 181650.640 181650.640 181650.640 181650.640 181650.640 0.006 0.006 0.006 1128.265 1128.265 1128.265 181650.640 181650.640 181650.640 1.000 1.000 1.000 1.000 1.000 181650.640 181650.640 181650.640 181650.640 181650.640 0.006 0.006 0.006 1128.265 1128.265 1128.265 181650.640 181650.640 181650.640 1.000 2.000 2.000 2.000 2.000 181650.640 451276.990 451276.990 451276.990 451276.990 0.012 0.012 0.012 2802.963 2802.963 2802.963 269626.350 269626.350 269626.350 1.000 1.000 1.000 1.000 1.000 181650.640 181650.640 181650.640 181650.640 181650.640 0.006 0.006 0.006 1128.265 1128.265 1128.265 181650.640 181650.640 181650.640
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91 403 CASH_OUT 79925.230 C1821775394 29889.000 0.000 C1000030947 962569.420 1042494.660 0 0 C1821775394_C1000030947 C1821775394_CASH_OUT C1000030947_CASH_OUT C1821775394_C1000030947_CASH_OUT 16.000 1.000 1.000 1.000 1.000 1.000 79925.230 79925.230 79925.230 79925.230 79925.230 0.006 0.004 0.003 475.745 333.022 237.873 79925.230 79925.230 79925.230 4.000 4.000 7.000 8.000 12.000 682116.440 682116.440 1338653.190 1880852.100 2417400.490 0.042 0.033 0.036 7968.174 7836.884 7194.644 361211.460 542198.910 542198.910 1.000 1.000 1.000 1.000 1.000 79925.230 79925.230 79925.230 79925.230 79925.230 0.006 0.004 0.003 475.745 333.022 237.873 79925.230 79925.230 79925.230 1.000 1.000 1.000 1.000 1.000 79925.230 79925.230 79925.230 79925.230 79925.230 0.006 0.004 0.003 475.745 333.022 237.873 79925.230 79925.230 79925.230 3.000 3.000 5.000 6.000 8.000 521733.830 521733.830 865756.730 1407955.640 1494460.160 0.030 0.025 0.024 5153.314 5866.482 4447.798 361211.460 542198.910 542198.910 1.000 1.000 1.000 1.000 1.000 79925.230 79925.230 79925.230 79925.230 79925.230 0.006 0.004 0.003 475.745 333.022 237.873 79925.230 79925.230 79925.230
92 690 CASH_IN 257271.670 C1617182604 6887317.410 7144589.080 C1000030947 1042494.660 785222.990 0 0 C1617182604_C1000030947 C1617182604_CASH_IN C1000030947_CASH_IN C1617182604_C1000030947_CASH_IN 28.000 1.000 1.000 1.000 1.000 1.000 257271.670 257271.670 257271.670 257271.670 257271.670 0.006 0.004 0.003 1531.379 1071.965 765.689 257271.670 257271.670 257271.670 1.000 1.000 1.000 1.000 5.000 257271.670 257271.670 257271.670 257271.670 939388.110 0.006 0.004 0.015 1531.379 1071.965 2795.798 257271.670 257271.670 361211.460 1.000 1.000 1.000 1.000 1.000 257271.670 257271.670 257271.670 257271.670 257271.670 0.006 0.004 0.003 1531.379 1071.965 765.689 257271.670 257271.670 257271.670 1.000 1.000 1.000 1.000 1.000 257271.670 257271.670 257271.670 257271.670 257271.670 0.006 0.004 0.003 1531.379 1071.965 765.689 257271.670 257271.670 257271.670 1.000 1.000 1.000 1.000 2.000 257271.670 257271.670 257271.670 257271.670 417654.280 0.006 0.004 0.006 1531.379 1071.965 1243.019 257271.670 257271.670 257271.670 1.000 1.000 1.000 1.000 1.000 257271.670 257271.670 257271.670 257271.670 257271.670 0.006 0.004 0.003 1531.379 1071.965 765.689 257271.670 257271.670 257271.670
93 397 CASH_OUT 47143.230 C1542679273 318299.520 271156.300 C100003532 0.000 47143.230 0 0 C1542679273_C100003532 C1542679273_CASH_OUT C100003532_CASH_OUT C1542679273_C100003532_CASH_OUT 16.000 1.000 1.000 1.000 1.000 1.000 47143.230 47143.230 47143.230 47143.230 47143.230 0.006 0.004 0.003 280.614 196.430 140.307 47143.230 47143.230 47143.230 1.000 1.000 1.000 1.000 1.000 47143.230 47143.230 47143.230 47143.230 47143.230 0.006 0.004 0.003 280.614 196.430 140.307 47143.230 47143.230 47143.230 1.000 1.000 1.000 1.000 1.000 47143.230 47143.230 47143.230 47143.230 47143.230 0.006 0.004 0.003 280.614 196.430 140.307 47143.230 47143.230 47143.230 1.000 1.000 1.000 1.000 1.000 47143.230 47143.230 47143.230 47143.230 47143.230 0.006 0.004 0.003 280.614 196.430 140.307 47143.230 47143.230 47143.230 1.000 1.000 1.000 1.000 1.000 47143.230 47143.230 47143.230 47143.230 47143.230 0.006 0.004 0.003 280.614 196.430 140.307 47143.230 47143.230 47143.230 1.000 1.000 1.000 1.000 1.000 47143.230 47143.230 47143.230 47143.230 47143.230 0.006 0.004 0.003 280.614 196.430 140.307 47143.230 47143.230 47143.230
94 12 CASH_IN 38909.170 C584476604 3085189.570 3124098.730 C1000038153 45497.000 0.000 0 0 C584476604_C1000038153 C584476604_CASH_IN C1000038153_CASH_IN C584476604_C1000038153_CASH_IN 0.000 1.000 1.000 1.000 1.000 1.000 38909.170 38909.170 38909.170 38909.170 38909.170 0.083 0.083 0.083 3242.431 3242.431 3242.431 38909.170 38909.170 38909.170 1.000 1.000 1.000 1.000 1.000 38909.170 38909.170 38909.170 38909.170 38909.170 0.083 0.083 0.083 3242.431 3242.431 3242.431 38909.170 38909.170 38909.170 1.000 1.000 1.000 1.000 1.000 38909.170 38909.170 38909.170 38909.170 38909.170 0.083 0.083 0.083 3242.431 3242.431 3242.431 38909.170 38909.170 38909.170 1.000 1.000 1.000 1.000 1.000 38909.170 38909.170 38909.170 38909.170 38909.170 0.083 0.083 0.083 3242.431 3242.431 3242.431 38909.170 38909.170 38909.170 1.000 1.000 1.000 1.000 1.000 38909.170 38909.170 38909.170 38909.170 38909.170 0.083 0.083 0.083 3242.431 3242.431 3242.431 38909.170 38909.170 38909.170 1.000 1.000 1.000 1.000 1.000 38909.170 38909.170 38909.170 38909.170 38909.170 0.083 0.083 0.083 3242.431 3242.431 3242.431 38909.170 38909.170 38909.170
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96 15 CASH_IN 128732.490 C1762848746 5704167.060 5832899.540 C1000038153 182158.710 53426.220 0 0 C1762848746_C1000038153 C1762848746_CASH_IN C1000038153_CASH_IN C1762848746_C1000038153_CASH_IN 0.000 1.000 1.000 1.000 1.000 1.000 128732.490 128732.490 128732.490 128732.490 128732.490 0.067 0.067 0.067 8582.166 8582.166 8582.166 128732.490 128732.490 128732.490 3.000 3.000 3.000 3.000 3.000 349800.370 349800.370 349800.370 349800.370 349800.370 0.200 0.200 0.200 23320.025 23320.025 23320.025 182158.710 182158.710 182158.710 1.000 1.000 1.000 1.000 1.000 128732.490 128732.490 128732.490 128732.490 128732.490 0.067 0.067 0.067 8582.166 8582.166 8582.166 128732.490 128732.490 128732.490 1.000 1.000 1.000 1.000 1.000 128732.490 128732.490 128732.490 128732.490 128732.490 0.067 0.067 0.067 8582.166 8582.166 8582.166 128732.490 128732.490 128732.490 2.000 2.000 2.000 2.000 2.000 167641.660 167641.660 167641.660 167641.660 167641.660 0.133 0.133 0.133 11176.111 11176.111 11176.111 128732.490 128732.490 128732.490 1.000 1.000 1.000 1.000 1.000 128732.490 128732.490 128732.490 128732.490 128732.490 0.067 0.067 0.067 8582.166 8582.166 8582.166 128732.490 128732.490 128732.490
97 17 CASH_IN 512143.380 C2037589604 29362.000 541505.380 C1000038153 53426.220 0.000 0 0 C2037589604_C1000038153 C2037589604_CASH_IN C1000038153_CASH_IN C2037589604_C1000038153_CASH_IN 0.000 1.000 1.000 1.000 1.000 1.000 512143.380 512143.380 512143.380 512143.380 512143.380 0.059 0.059 0.059 30126.081 30126.081 30126.081 512143.380 512143.380 512143.380 4.000 4.000 4.000 4.000 4.000 861943.750 861943.750 861943.750 861943.750 861943.750 0.235 0.235 0.235 50702.574 50702.574 50702.574 512143.380 512143.380 512143.380 1.000 1.000 1.000 1.000 1.000 512143.380 512143.380 512143.380 512143.380 512143.380 0.059 0.059 0.059 30126.081 30126.081 30126.081 512143.380 512143.380 512143.380 1.000 1.000 1.000 1.000 1.000 512143.380 512143.380 512143.380 512143.380 512143.380 0.059 0.059 0.059 30126.081 30126.081 30126.081 512143.380 512143.380 512143.380 3.000 3.000 3.000 3.000 3.000 679785.040 679785.040 679785.040 679785.040 679785.040 0.176 0.176 0.176 39987.355 39987.355 39987.355 512143.380 512143.380 512143.380 1.000 1.000 1.000 1.000 1.000 512143.380 512143.380 512143.380 512143.380 512143.380 0.059 0.059 0.059 30126.081 30126.081 30126.081 512143.380 512143.380 512143.380
98 139 CASH_OUT 15706.950 C1882207334 99775.000 84068.050 C1000038153 0.000 15706.950 0 0 C1882207334_C1000038153 C1882207334_CASH_OUT C1000038153_CASH_OUT C1882207334_C1000038153_CASH_OUT 5.000 1.000 1.000 1.000 1.000 1.000 15706.950 15706.950 15706.950 15706.950 15706.950 0.007 0.007 0.007 113.000 113.000 113.000 15706.950 15706.950 15706.950 1.000 1.000 5.000 5.000 5.000 15706.950 15706.950 877650.700 877650.700 877650.700 0.036 0.036 0.036 6314.034 6314.034 6314.034 512143.380 512143.380 512143.380 1.000 1.000 1.000 1.000 1.000 15706.950 15706.950 15706.950 15706.950 15706.950 0.007 0.007 0.007 113.000 113.000 113.000 15706.950 15706.950 15706.950 1.000 1.000 1.000 1.000 1.000 15706.950 15706.950 15706.950 15706.950 15706.950 0.007 0.007 0.007 113.000 113.000 113.000 15706.950 15706.950 15706.950 1.000 1.000 2.000 2.000 2.000 15706.950 15706.950 197865.660 197865.660 197865.660 0.014 0.014 0.014 1423.494 1423.494 1423.494 182158.710 182158.710 182158.710 1.000 1.000 1.000 1.000 1.000 15706.950 15706.950 15706.950 15706.950 15706.950 0.007 0.007 0.007 113.000 113.000 113.000 15706.950 15706.950 15706.950
99 156 DEBIT 4939.320 C1913815827 30880.000 25940.680 C1000038153 15706.950 20646.270 0 0 C1913815827_C1000038153 C1913815827_DEBIT C1000038153_DEBIT C1913815827_C1000038153_DEBIT 6.000 1.000 1.000 1.000 1.000 1.000 4939.320 4939.320 4939.320 4939.320 4939.320 0.006 0.006 0.006 31.662 31.662 31.662 4939.320 4939.320 4939.320 2.000 2.000 6.000 6.000 6.000 20646.270 20646.270 882590.020 882590.020 882590.020 0.038 0.038 0.038 5657.628 5657.628 5657.628 512143.380 512143.380 512143.380 1.000 1.000 1.000 1.000 1.000 4939.320 4939.320 4939.320 4939.320 4939.320 0.006 0.006 0.006 31.662 31.662 31.662 4939.320 4939.320 4939.320 1.000 1.000 1.000 1.000 1.000 4939.320 4939.320 4939.320 4939.320 4939.320 0.006 0.006 0.006 31.662 31.662 31.662 4939.320 4939.320 4939.320 1.000 1.000 1.000 1.000 1.000 4939.320 4939.320 4939.320 4939.320 4939.320 0.006 0.006 0.006 31.662 31.662 31.662 4939.320 4939.320 4939.320 1.000 1.000 1.000 1.000 1.000 4939.320 4939.320 4939.320 4939.320 4939.320 0.006 0.006 0.006 31.662 31.662 31.662 4939.320 4939.320 4939.320
In [30]:
#aml_data[aml_data.nameDest == 'C1023714065']
aml_data[aml_data.nameDest == 'C1017189714']
Out[30]:
step type amount nameOrig oldbalanceOrg newbalanceOrig nameDest oldbalanceDest newbalanceDest isFraud isFlaggedFraud nameOrig_nameDest nameOrig_type nameDest_type nameOrig_nameDest_type day nameOrig_rolling_txn_count_1day nameOrig_rolling_txn_count_3day nameOrig_rolling_txn_count_7day nameOrig_rolling_txn_count_10day nameOrig_rolling_txn_count_14day nameOrig_rolling_txn_sum_1day nameOrig_rolling_txn_sum_3day nameOrig_rolling_txn_sum_7day nameOrig_rolling_txn_sum_10day nameOrig_rolling_txn_sum_14day nameOrig_rolling_txn_count_mean_7day nameOrig_rolling_txn_count_mean_10day nameOrig_rolling_txn_count_mean_14day nameOrig_rolling_txn_amount_mean_7day nameOrig_rolling_txn_amount_mean_10day nameOrig_rolling_txn_amount_mean_14day nameOrig_rolling_txn_amount_max_7day nameOrig_rolling_txn_amount_max_10day nameOrig_rolling_txn_amount_max_14day nameDest_rolling_txn_count_1day nameDest_rolling_txn_count_3day nameDest_rolling_txn_count_7day nameDest_rolling_txn_count_10day nameDest_rolling_txn_count_14day nameDest_rolling_txn_sum_1day nameDest_rolling_txn_sum_3day nameDest_rolling_txn_sum_7day nameDest_rolling_txn_sum_10day nameDest_rolling_txn_sum_14day nameDest_rolling_txn_count_mean_7day nameDest_rolling_txn_count_mean_10day nameDest_rolling_txn_count_mean_14day nameDest_rolling_txn_amount_mean_7day nameDest_rolling_txn_amount_mean_10day nameDest_rolling_txn_amount_mean_14day nameDest_rolling_txn_amount_max_7day nameDest_rolling_txn_amount_max_10day nameDest_rolling_txn_amount_max_14day nameOrig_nameDest_rolling_txn_count_1day nameOrig_nameDest_rolling_txn_count_3day nameOrig_nameDest_rolling_txn_count_7day nameOrig_nameDest_rolling_txn_count_10day nameOrig_nameDest_rolling_txn_count_14day nameOrig_nameDest_rolling_txn_sum_1day nameOrig_nameDest_rolling_txn_sum_3day nameOrig_nameDest_rolling_txn_sum_7day nameOrig_nameDest_rolling_txn_sum_10day nameOrig_nameDest_rolling_txn_sum_14day nameOrig_nameDest_rolling_txn_count_mean_7day nameOrig_nameDest_rolling_txn_count_mean_10day nameOrig_nameDest_rolling_txn_count_mean_14day nameOrig_nameDest_rolling_txn_amount_mean_7day nameOrig_nameDest_rolling_txn_amount_mean_10day nameOrig_nameDest_rolling_txn_amount_mean_14day nameOrig_nameDest_rolling_txn_amount_max_7day nameOrig_nameDest_rolling_txn_amount_max_10day nameOrig_nameDest_rolling_txn_amount_max_14day nameOrig_type_rolling_txn_count_1day nameOrig_type_rolling_txn_count_3day nameOrig_type_rolling_txn_count_7day nameOrig_type_rolling_txn_count_10day nameOrig_type_rolling_txn_count_14day nameOrig_type_rolling_txn_sum_1day nameOrig_type_rolling_txn_sum_3day nameOrig_type_rolling_txn_sum_7day nameOrig_type_rolling_txn_sum_10day nameOrig_type_rolling_txn_sum_14day nameOrig_type_rolling_txn_count_mean_7day nameOrig_type_rolling_txn_count_mean_10day nameOrig_type_rolling_txn_count_mean_14day nameOrig_type_rolling_txn_amount_mean_7day nameOrig_type_rolling_txn_amount_mean_10day nameOrig_type_rolling_txn_amount_mean_14day nameOrig_type_rolling_txn_amount_max_7day nameOrig_type_rolling_txn_amount_max_10day nameOrig_type_rolling_txn_amount_max_14day nameDest_type_rolling_txn_count_1day nameDest_type_rolling_txn_count_3day nameDest_type_rolling_txn_count_7day nameDest_type_rolling_txn_count_10day nameDest_type_rolling_txn_count_14day nameDest_type_rolling_txn_sum_1day nameDest_type_rolling_txn_sum_3day nameDest_type_rolling_txn_sum_7day nameDest_type_rolling_txn_sum_10day nameDest_type_rolling_txn_sum_14day nameDest_type_rolling_txn_count_mean_7day nameDest_type_rolling_txn_count_mean_10day nameDest_type_rolling_txn_count_mean_14day nameDest_type_rolling_txn_amount_mean_7day nameDest_type_rolling_txn_amount_mean_10day nameDest_type_rolling_txn_amount_mean_14day nameDest_type_rolling_txn_amount_max_7day nameDest_type_rolling_txn_amount_max_10day nameDest_type_rolling_txn_amount_max_14day nameOrig_nameDest_type_rolling_txn_count_1day nameOrig_nameDest_type_rolling_txn_count_3day nameOrig_nameDest_type_rolling_txn_count_7day nameOrig_nameDest_type_rolling_txn_count_10day nameOrig_nameDest_type_rolling_txn_count_14day nameOrig_nameDest_type_rolling_txn_sum_1day nameOrig_nameDest_type_rolling_txn_sum_3day nameOrig_nameDest_type_rolling_txn_sum_7day nameOrig_nameDest_type_rolling_txn_sum_10day nameOrig_nameDest_type_rolling_txn_sum_14day nameOrig_nameDest_type_rolling_txn_count_mean_7day nameOrig_nameDest_type_rolling_txn_count_mean_10day nameOrig_nameDest_type_rolling_txn_count_mean_14day nameOrig_nameDest_type_rolling_txn_amount_mean_7day nameOrig_nameDest_type_rolling_txn_amount_mean_10day nameOrig_nameDest_type_rolling_txn_amount_mean_14day nameOrig_nameDest_type_rolling_txn_amount_max_7day nameOrig_nameDest_type_rolling_txn_amount_max_10day nameOrig_nameDest_type_rolling_txn_amount_max_14day
38539 228 CASH_OUT 336755.810 C796280164 4060.000 0.000 C1017189714 0.000 336755.810 0 0 C796280164_C1017189714 C796280164_CASH_OUT C1017189714_CASH_OUT C796280164_C1017189714_CASH_OUT 9.000 1.000 1.000 1.000 1.000 1.000 336755.810 336755.810 336755.810 336755.810 336755.810 0.006 0.004 0.004 2004.499 1476.999 1476.999 336755.810 336755.810 336755.810 1.000 1.000 1.000 1.000 1.000 336755.810 336755.810 336755.810 336755.810 336755.810 0.006 0.004 0.004 2004.499 1476.999 1476.999 336755.810 336755.810 336755.810 1.000 1.000 1.000 1.000 1.000 336755.810 336755.810 336755.810 336755.810 336755.810 0.006 0.004 0.004 2004.499 1476.999 1476.999 336755.810 336755.810 336755.810 1.000 1.000 1.000 1.000 1.000 336755.810 336755.810 336755.810 336755.810 336755.810 0.006 0.004 0.004 2004.499 1476.999 1476.999 336755.810 336755.810 336755.810 1.000 1.000 1.000 1.000 1.000 336755.810 336755.810 336755.810 336755.810 336755.810 0.006 0.004 0.004 2004.499 1476.999 1476.999 336755.810 336755.810 336755.810 1.000 1.000 1.000 1.000 1.000 336755.810 336755.810 336755.810 336755.810 336755.810 0.006 0.004 0.004 2004.499 1476.999 1476.999 336755.810 336755.810 336755.810
38540 241 CASH_IN 151893.230 C1106806499 5128631.210 5280524.440 C1017189714 336755.810 184862.580 0 0 C1106806499_C1017189714 C1106806499_CASH_IN C1017189714_CASH_IN C1106806499_C1017189714_CASH_IN 10.000 1.000 1.000 1.000 1.000 1.000 151893.230 151893.230 151893.230 151893.230 151893.230 0.006 0.004 0.004 904.126 632.888 630.262 151893.230 151893.230 151893.230 2.000 2.000 2.000 2.000 2.000 488649.040 488649.040 488649.040 488649.040 488649.040 0.012 0.008 0.008 2908.625 2036.038 2027.589 336755.810 336755.810 336755.810 1.000 1.000 1.000 1.000 1.000 151893.230 151893.230 151893.230 151893.230 151893.230 0.006 0.004 0.004 904.126 632.888 630.262 151893.230 151893.230 151893.230 1.000 1.000 1.000 1.000 1.000 151893.230 151893.230 151893.230 151893.230 151893.230 0.006 0.004 0.004 904.126 632.888 630.262 151893.230 151893.230 151893.230 1.000 1.000 1.000 1.000 1.000 151893.230 151893.230 151893.230 151893.230 151893.230 0.006 0.004 0.004 904.126 632.888 630.262 151893.230 151893.230 151893.230 1.000 1.000 1.000 1.000 1.000 151893.230 151893.230 151893.230 151893.230 151893.230 0.006 0.004 0.004 904.126 632.888 630.262 151893.230 151893.230 151893.230
38541 251 CASH_OUT 53055.780 C805734556 45202.000 0.000 C1017189714 184862.580 122152.630 0 0 C805734556_C1017189714 C805734556_CASH_OUT C1017189714_CASH_OUT C805734556_C1017189714_CASH_OUT 10.000 1.000 1.000 1.000 1.000 1.000 53055.780 53055.780 53055.780 53055.780 53055.780 0.006 0.004 0.004 315.808 221.066 211.378 53055.780 53055.780 53055.780 3.000 3.000 3.000 3.000 3.000 541704.820 541704.820 541704.820 541704.820 541704.820 0.018 0.013 0.012 3224.433 2257.103 2158.187 336755.810 336755.810 336755.810 1.000 1.000 1.000 1.000 1.000 53055.780 53055.780 53055.780 53055.780 53055.780 0.006 0.004 0.004 315.808 221.066 211.378 53055.780 53055.780 53055.780 1.000 1.000 1.000 1.000 1.000 53055.780 53055.780 53055.780 53055.780 53055.780 0.006 0.004 0.004 315.808 221.066 211.378 53055.780 53055.780 53055.780 2.000 2.000 2.000 2.000 2.000 389811.590 389811.590 389811.590 389811.590 389811.590 0.012 0.008 0.008 2320.307 1624.215 1553.034 336755.810 336755.810 336755.810 1.000 1.000 1.000 1.000 1.000 53055.780 53055.780 53055.780 53055.780 53055.780 0.006 0.004 0.004 315.808 221.066 211.378 53055.780 53055.780 53055.780
38542 252 CASH_IN 115765.730 C76725420 6875447.480 6991213.220 C1017189714 237918.360 122152.630 0 0 C76725420_C1017189714 C76725420_CASH_IN C1017189714_CASH_IN C76725420_C1017189714_CASH_IN 10.000 1.000 1.000 1.000 1.000 1.000 115765.730 115765.730 115765.730 115765.730 115765.730 0.006 0.004 0.004 689.082 482.357 459.388 115765.730 115765.730 115765.730 3.000 4.000 4.000 4.000 4.000 320714.740 657470.550 657470.550 657470.550 657470.550 0.024 0.017 0.016 3913.515 2739.461 2609.010 336755.810 336755.810 336755.810 1.000 1.000 1.000 1.000 1.000 115765.730 115765.730 115765.730 115765.730 115765.730 0.006 0.004 0.004 689.082 482.357 459.388 115765.730 115765.730 115765.730 1.000 1.000 1.000 1.000 1.000 115765.730 115765.730 115765.730 115765.730 115765.730 0.006 0.004 0.004 689.082 482.357 459.388 115765.730 115765.730 115765.730 2.000 2.000 2.000 2.000 2.000 267658.960 267658.960 267658.960 267658.960 267658.960 0.012 0.008 0.008 1593.208 1115.246 1062.139 151893.230 151893.230 151893.230 1.000 1.000 1.000 1.000 1.000 115765.730 115765.730 115765.730 115765.730 115765.730 0.006 0.004 0.004 689.082 482.357 459.388 115765.730 115765.730 115765.730
38543 253 CASH_OUT 143021.030 C999881658 10144.000 0.000 C1017189714 122152.630 265173.650 0 0 C999881658_C1017189714 C999881658_CASH_OUT C1017189714_CASH_OUT C999881658_C1017189714_CASH_OUT 10.000 1.000 1.000 1.000 1.000 1.000 143021.030 143021.030 143021.030 143021.030 143021.030 0.006 0.004 0.004 851.316 595.921 565.301 143021.030 143021.030 143021.030 4.000 5.000 5.000 5.000 5.000 463735.770 800491.580 800491.580 800491.580 800491.580 0.030 0.021 0.020 4764.831 3335.382 3163.998 336755.810 336755.810 336755.810 1.000 1.000 1.000 1.000 1.000 143021.030 143021.030 143021.030 143021.030 143021.030 0.006 0.004 0.004 851.316 595.921 565.301 143021.030 143021.030 143021.030 1.000 1.000 1.000 1.000 1.000 143021.030 143021.030 143021.030 143021.030 143021.030 0.006 0.004 0.004 851.316 595.921 565.301 143021.030 143021.030 143021.030 2.000 3.000 3.000 3.000 3.000 196076.810 532832.620 532832.620 532832.620 532832.620 0.018 0.013 0.012 3171.623 2220.136 2106.058 336755.810 336755.810 336755.810 1.000 1.000 1.000 1.000 1.000 143021.030 143021.030 143021.030 143021.030 143021.030 0.006 0.004 0.004 851.316 595.921 565.301 143021.030 143021.030 143021.030
38544 304 CASH_IN 261072.400 C1990589144 843272.920 1104345.320 C1017189714 265173.650 4101.260 0 0 C1990589144_C1017189714 C1990589144_CASH_IN C1017189714_CASH_IN C1990589144_C1017189714_CASH_IN 12.000 1.000 1.000 1.000 1.000 1.000 261072.400 261072.400 261072.400 261072.400 261072.400 0.006 0.004 0.003 1554.002 1087.802 858.791 261072.400 261072.400 261072.400 1.000 5.000 6.000 6.000 6.000 261072.400 724808.170 1061563.980 1061563.980 1061563.980 0.036 0.025 0.020 6318.833 4423.183 3491.987 336755.810 336755.810 336755.810 1.000 1.000 1.000 1.000 1.000 261072.400 261072.400 261072.400 261072.400 261072.400 0.006 0.004 0.003 1554.002 1087.802 858.791 261072.400 261072.400 261072.400 1.000 1.000 1.000 1.000 1.000 261072.400 261072.400 261072.400 261072.400 261072.400 0.006 0.004 0.003 1554.002 1087.802 858.791 261072.400 261072.400 261072.400 1.000 3.000 3.000 3.000 3.000 261072.400 528731.360 528731.360 528731.360 528731.360 0.018 0.013 0.010 3147.210 2203.047 1739.248 261072.400 261072.400 261072.400 1.000 1.000 1.000 1.000 1.000 261072.400 261072.400 261072.400 261072.400 261072.400 0.006 0.004 0.003 1554.002 1087.802 858.791 261072.400 261072.400 261072.400
38545 379 CASH_OUT 148295.940 C1864196551 79628.000 0.000 C1017189714 4101.260 152397.200 0 0 C1864196551_C1017189714 C1864196551_CASH_OUT C1017189714_CASH_OUT C1864196551_C1017189714_CASH_OUT 15.000 1.000 1.000 1.000 1.000 1.000 148295.940 148295.940 148295.940 148295.940 148295.940 0.006 0.004 0.003 882.714 617.900 441.357 148295.940 148295.940 148295.940 1.000 1.000 7.000 7.000 7.000 148295.940 148295.940 1209859.920 1209859.920 1209859.920 0.042 0.029 0.021 7201.547 5041.083 3600.774 336755.810 336755.810 336755.810 1.000 1.000 1.000 1.000 1.000 148295.940 148295.940 148295.940 148295.940 148295.940 0.006 0.004 0.003 882.714 617.900 441.357 148295.940 148295.940 148295.940 1.000 1.000 1.000 1.000 1.000 148295.940 148295.940 148295.940 148295.940 148295.940 0.006 0.004 0.003 882.714 617.900 441.357 148295.940 148295.940 148295.940 1.000 1.000 4.000 4.000 4.000 148295.940 148295.940 681128.560 681128.560 681128.560 0.024 0.017 0.012 4054.337 2838.036 2027.168 336755.810 336755.810 336755.810 1.000 1.000 1.000 1.000 1.000 148295.940 148295.940 148295.940 148295.940 148295.940 0.006 0.004 0.003 882.714 617.900 441.357 148295.940 148295.940 148295.940
In [31]:
aml_data[aml_data.isFraud == 1].head(100)
Out[31]:
step type amount nameOrig oldbalanceOrg newbalanceOrig nameDest oldbalanceDest newbalanceDest isFraud isFlaggedFraud nameOrig_nameDest nameOrig_type nameDest_type nameOrig_nameDest_type day nameOrig_rolling_txn_count_1day nameOrig_rolling_txn_count_3day nameOrig_rolling_txn_count_7day nameOrig_rolling_txn_count_10day nameOrig_rolling_txn_count_14day nameOrig_rolling_txn_sum_1day nameOrig_rolling_txn_sum_3day nameOrig_rolling_txn_sum_7day nameOrig_rolling_txn_sum_10day nameOrig_rolling_txn_sum_14day nameOrig_rolling_txn_count_mean_7day nameOrig_rolling_txn_count_mean_10day nameOrig_rolling_txn_count_mean_14day nameOrig_rolling_txn_amount_mean_7day nameOrig_rolling_txn_amount_mean_10day nameOrig_rolling_txn_amount_mean_14day nameOrig_rolling_txn_amount_max_7day nameOrig_rolling_txn_amount_max_10day nameOrig_rolling_txn_amount_max_14day nameDest_rolling_txn_count_1day nameDest_rolling_txn_count_3day nameDest_rolling_txn_count_7day nameDest_rolling_txn_count_10day nameDest_rolling_txn_count_14day nameDest_rolling_txn_sum_1day nameDest_rolling_txn_sum_3day nameDest_rolling_txn_sum_7day nameDest_rolling_txn_sum_10day nameDest_rolling_txn_sum_14day nameDest_rolling_txn_count_mean_7day nameDest_rolling_txn_count_mean_10day nameDest_rolling_txn_count_mean_14day nameDest_rolling_txn_amount_mean_7day nameDest_rolling_txn_amount_mean_10day nameDest_rolling_txn_amount_mean_14day nameDest_rolling_txn_amount_max_7day nameDest_rolling_txn_amount_max_10day nameDest_rolling_txn_amount_max_14day nameOrig_nameDest_rolling_txn_count_1day nameOrig_nameDest_rolling_txn_count_3day nameOrig_nameDest_rolling_txn_count_7day nameOrig_nameDest_rolling_txn_count_10day nameOrig_nameDest_rolling_txn_count_14day nameOrig_nameDest_rolling_txn_sum_1day nameOrig_nameDest_rolling_txn_sum_3day nameOrig_nameDest_rolling_txn_sum_7day nameOrig_nameDest_rolling_txn_sum_10day nameOrig_nameDest_rolling_txn_sum_14day nameOrig_nameDest_rolling_txn_count_mean_7day nameOrig_nameDest_rolling_txn_count_mean_10day nameOrig_nameDest_rolling_txn_count_mean_14day nameOrig_nameDest_rolling_txn_amount_mean_7day nameOrig_nameDest_rolling_txn_amount_mean_10day nameOrig_nameDest_rolling_txn_amount_mean_14day nameOrig_nameDest_rolling_txn_amount_max_7day nameOrig_nameDest_rolling_txn_amount_max_10day nameOrig_nameDest_rolling_txn_amount_max_14day nameOrig_type_rolling_txn_count_1day nameOrig_type_rolling_txn_count_3day nameOrig_type_rolling_txn_count_7day nameOrig_type_rolling_txn_count_10day nameOrig_type_rolling_txn_count_14day nameOrig_type_rolling_txn_sum_1day nameOrig_type_rolling_txn_sum_3day nameOrig_type_rolling_txn_sum_7day nameOrig_type_rolling_txn_sum_10day nameOrig_type_rolling_txn_sum_14day nameOrig_type_rolling_txn_count_mean_7day nameOrig_type_rolling_txn_count_mean_10day nameOrig_type_rolling_txn_count_mean_14day nameOrig_type_rolling_txn_amount_mean_7day nameOrig_type_rolling_txn_amount_mean_10day nameOrig_type_rolling_txn_amount_mean_14day nameOrig_type_rolling_txn_amount_max_7day nameOrig_type_rolling_txn_amount_max_10day nameOrig_type_rolling_txn_amount_max_14day nameDest_type_rolling_txn_count_1day nameDest_type_rolling_txn_count_3day nameDest_type_rolling_txn_count_7day nameDest_type_rolling_txn_count_10day nameDest_type_rolling_txn_count_14day nameDest_type_rolling_txn_sum_1day nameDest_type_rolling_txn_sum_3day nameDest_type_rolling_txn_sum_7day nameDest_type_rolling_txn_sum_10day nameDest_type_rolling_txn_sum_14day nameDest_type_rolling_txn_count_mean_7day nameDest_type_rolling_txn_count_mean_10day nameDest_type_rolling_txn_count_mean_14day nameDest_type_rolling_txn_amount_mean_7day nameDest_type_rolling_txn_amount_mean_10day nameDest_type_rolling_txn_amount_mean_14day nameDest_type_rolling_txn_amount_max_7day nameDest_type_rolling_txn_amount_max_10day nameDest_type_rolling_txn_amount_max_14day nameOrig_nameDest_type_rolling_txn_count_1day nameOrig_nameDest_type_rolling_txn_count_3day nameOrig_nameDest_type_rolling_txn_count_7day nameOrig_nameDest_type_rolling_txn_count_10day nameOrig_nameDest_type_rolling_txn_count_14day nameOrig_nameDest_type_rolling_txn_sum_1day nameOrig_nameDest_type_rolling_txn_sum_3day nameOrig_nameDest_type_rolling_txn_sum_7day nameOrig_nameDest_type_rolling_txn_sum_10day nameOrig_nameDest_type_rolling_txn_sum_14day nameOrig_nameDest_type_rolling_txn_count_mean_7day nameOrig_nameDest_type_rolling_txn_count_mean_10day nameOrig_nameDest_type_rolling_txn_count_mean_14day nameOrig_nameDest_type_rolling_txn_amount_mean_7day nameOrig_nameDest_type_rolling_txn_amount_mean_10day nameOrig_nameDest_type_rolling_txn_amount_mean_14day nameOrig_nameDest_type_rolling_txn_amount_max_7day nameOrig_nameDest_type_rolling_txn_amount_max_10day nameOrig_nameDest_type_rolling_txn_amount_max_14day
126 270 TRANSFER 134623.950 C1664606481 134623.950 0.000 C1000039615 0.000 0.000 1 0 C1664606481_C1000039615 C1664606481_TRANSFER C1000039615_TRANSFER C1664606481_C1000039615_TRANSFER 11.000 1.000 1.000 1.000 1.000 1.000 134623.950 134623.950 134623.950 134623.950 134623.950 0.006 0.004 0.004 801.333 560.933 498.607 134623.950 134623.950 134623.950 1.000 1.000 1.000 1.000 1.000 134623.950 134623.950 134623.950 134623.950 134623.950 0.006 0.004 0.004 801.333 560.933 498.607 134623.950 134623.950 134623.950 1.000 1.000 1.000 1.000 1.000 134623.950 134623.950 134623.950 134623.950 134623.950 0.006 0.004 0.004 801.333 560.933 498.607 134623.950 134623.950 134623.950 1.000 1.000 1.000 1.000 1.000 134623.950 134623.950 134623.950 134623.950 134623.950 0.006 0.004 0.004 801.333 560.933 498.607 134623.950 134623.950 134623.950 1.000 1.000 1.000 1.000 1.000 134623.950 134623.950 134623.950 134623.950 134623.950 0.006 0.004 0.004 801.333 560.933 498.607 134623.950 134623.950 134623.950 1.000 1.000 1.000 1.000 1.000 134623.950 134623.950 134623.950 134623.950 134623.950 0.006 0.004 0.004 801.333 560.933 498.607 134623.950 134623.950 134623.950
929 578 TRANSFER 190815.790 C1501869620 190815.790 0.000 C1000367306 0.000 0.000 1 0 C1501869620_C1000367306 C1501869620_TRANSFER C1000367306_TRANSFER C1501869620_C1000367306_TRANSFER 24.000 1.000 1.000 1.000 1.000 1.000 190815.790 190815.790 190815.790 190815.790 190815.790 0.006 0.004 0.003 1135.808 795.066 567.904 190815.790 190815.790 190815.790 1.000 1.000 1.000 1.000 1.000 190815.790 190815.790 190815.790 190815.790 190815.790 0.006 0.004 0.003 1135.808 795.066 567.904 190815.790 190815.790 190815.790 1.000 1.000 1.000 1.000 1.000 190815.790 190815.790 190815.790 190815.790 190815.790 0.006 0.004 0.003 1135.808 795.066 567.904 190815.790 190815.790 190815.790 1.000 1.000 1.000 1.000 1.000 190815.790 190815.790 190815.790 190815.790 190815.790 0.006 0.004 0.003 1135.808 795.066 567.904 190815.790 190815.790 190815.790 1.000 1.000 1.000 1.000 1.000 190815.790 190815.790 190815.790 190815.790 190815.790 0.006 0.004 0.003 1135.808 795.066 567.904 190815.790 190815.790 190815.790 1.000 1.000 1.000 1.000 1.000 190815.790 190815.790 190815.790 190815.790 190815.790 0.006 0.004 0.003 1135.808 795.066 567.904 190815.790 190815.790 190815.790
1030 637 TRANSFER 3845765.360 C196788126 3845765.360 0.000 C1000407130 0.000 0.000 1 0 C196788126_C1000407130 C196788126_TRANSFER C1000407130_TRANSFER C196788126_C1000407130_TRANSFER 26.000 1.000 1.000 1.000 1.000 1.000 3845765.360 3845765.360 3845765.360 3845765.360 3845765.360 0.006 0.004 0.003 22891.460 16024.022 11445.730 3845765.360 3845765.360 3845765.360 1.000 1.000 1.000 1.000 1.000 3845765.360 3845765.360 3845765.360 3845765.360 3845765.360 0.006 0.004 0.003 22891.460 16024.022 11445.730 3845765.360 3845765.360 3845765.360 1.000 1.000 1.000 1.000 1.000 3845765.360 3845765.360 3845765.360 3845765.360 3845765.360 0.006 0.004 0.003 22891.460 16024.022 11445.730 3845765.360 3845765.360 3845765.360 1.000 1.000 1.000 1.000 1.000 3845765.360 3845765.360 3845765.360 3845765.360 3845765.360 0.006 0.004 0.003 22891.460 16024.022 11445.730 3845765.360 3845765.360 3845765.360 1.000 1.000 1.000 1.000 1.000 3845765.360 3845765.360 3845765.360 3845765.360 3845765.360 0.006 0.004 0.003 22891.460 16024.022 11445.730 3845765.360 3845765.360 3845765.360 1.000 1.000 1.000 1.000 1.000 3845765.360 3845765.360 3845765.360 3845765.360 3845765.360 0.006 0.004 0.003 22891.460 16024.022 11445.730 3845765.360 3845765.360 3845765.360
2087 579 TRANSFER 1632500.220 C1055490123 1632500.220 0.000 C1000836187 0.000 0.000 1 0 C1055490123_C1000836187 C1055490123_TRANSFER C1000836187_TRANSFER C1055490123_C1000836187_TRANSFER 24.000 1.000 1.000 1.000 1.000 1.000 1632500.220 1632500.220 1632500.220 1632500.220 1632500.220 0.006 0.004 0.003 9717.263 6802.084 4858.632 1632500.220 1632500.220 1632500.220 1.000 1.000 1.000 1.000 1.000 1632500.220 1632500.220 1632500.220 1632500.220 1632500.220 0.006 0.004 0.003 9717.263 6802.084 4858.632 1632500.220 1632500.220 1632500.220 1.000 1.000 1.000 1.000 1.000 1632500.220 1632500.220 1632500.220 1632500.220 1632500.220 0.006 0.004 0.003 9717.263 6802.084 4858.632 1632500.220 1632500.220 1632500.220 1.000 1.000 1.000 1.000 1.000 1632500.220 1632500.220 1632500.220 1632500.220 1632500.220 0.006 0.004 0.003 9717.263 6802.084 4858.632 1632500.220 1632500.220 1632500.220 1.000 1.000 1.000 1.000 1.000 1632500.220 1632500.220 1632500.220 1632500.220 1632500.220 0.006 0.004 0.003 9717.263 6802.084 4858.632 1632500.220 1632500.220 1632500.220 1.000 1.000 1.000 1.000 1.000 1632500.220 1632500.220 1632500.220 1632500.220 1632500.220 0.006 0.004 0.003 9717.263 6802.084 4858.632 1632500.220 1632500.220 1632500.220
2207 217 TRANSFER 972713.050 C706587857 972713.050 0.000 C1000855680 0.000 0.000 1 0 C706587857_C1000855680 C706587857_TRANSFER C1000855680_TRANSFER C706587857_C1000855680_TRANSFER 9.000 1.000 1.000 1.000 1.000 1.000 972713.050 972713.050 972713.050 972713.050 972713.050 0.006 0.005 0.005 5789.959 4482.549 4482.549 972713.050 972713.050 972713.050 1.000 1.000 1.000 1.000 1.000 972713.050 972713.050 972713.050 972713.050 972713.050 0.006 0.005 0.005 5789.959 4482.549 4482.549 972713.050 972713.050 972713.050 1.000 1.000 1.000 1.000 1.000 972713.050 972713.050 972713.050 972713.050 972713.050 0.006 0.005 0.005 5789.959 4482.549 4482.549 972713.050 972713.050 972713.050 1.000 1.000 1.000 1.000 1.000 972713.050 972713.050 972713.050 972713.050 972713.050 0.006 0.005 0.005 5789.959 4482.549 4482.549 972713.050 972713.050 972713.050 1.000 1.000 1.000 1.000 1.000 972713.050 972713.050 972713.050 972713.050 972713.050 0.006 0.005 0.005 5789.959 4482.549 4482.549 972713.050 972713.050 972713.050 1.000 1.000 1.000 1.000 1.000 972713.050 972713.050 972713.050 972713.050 972713.050 0.006 0.005 0.005 5789.959 4482.549 4482.549 972713.050 972713.050 972713.050
2241 398 TRANSFER 10000000.000 C14368419 25618179.900 15618179.900 C1000868784 0.000 0.000 1 0 C14368419_C1000868784 C14368419_TRANSFER C1000868784_TRANSFER C14368419_C1000868784_TRANSFER 16.000 1.000 1.000 1.000 1.000 1.000 10000000.000 10000000.000 10000000.000 10000000.000 10000000.000 0.006 0.004 0.003 59523.810 41666.667 29761.905 10000000.000 10000000.000 10000000.000 1.000 1.000 1.000 1.000 1.000 10000000.000 10000000.000 10000000.000 10000000.000 10000000.000 0.006 0.004 0.003 59523.810 41666.667 29761.905 10000000.000 10000000.000 10000000.000 1.000 1.000 1.000 1.000 1.000 10000000.000 10000000.000 10000000.000 10000000.000 10000000.000 0.006 0.004 0.003 59523.810 41666.667 29761.905 10000000.000 10000000.000 10000000.000 1.000 1.000 1.000 1.000 1.000 10000000.000 10000000.000 10000000.000 10000000.000 10000000.000 0.006 0.004 0.003 59523.810 41666.667 29761.905 10000000.000 10000000.000 10000000.000 1.000 1.000 1.000 1.000 1.000 10000000.000 10000000.000 10000000.000 10000000.000 10000000.000 0.006 0.004 0.003 59523.810 41666.667 29761.905 10000000.000 10000000.000 10000000.000 1.000 1.000 1.000 1.000 1.000 10000000.000 10000000.000 10000000.000 10000000.000 10000000.000 0.006 0.004 0.003 59523.810 41666.667 29761.905 10000000.000 10000000.000 10000000.000
3271 569 CASH_OUT 15093.690 C200350640 15093.690 0.000 C1001258143 700860.280 715953.970 1 0 C200350640_C1001258143 C200350640_CASH_OUT C1001258143_CASH_OUT C200350640_C1001258143_CASH_OUT 23.000 1.000 1.000 1.000 1.000 1.000 15093.690 15093.690 15093.690 15093.690 15093.690 0.006 0.004 0.003 89.843 62.890 44.922 15093.690 15093.690 15093.690 1.000 1.000 2.000 3.000 9.000 15093.690 15093.690 229418.080 421595.490 1709719.260 0.012 0.013 0.027 1365.584 1756.648 5088.450 214324.390 214324.390 478907.780 1.000 1.000 1.000 1.000 1.000 15093.690 15093.690 15093.690 15093.690 15093.690 0.006 0.004 0.003 89.843 62.890 44.922 15093.690 15093.690 15093.690 1.000 1.000 1.000 1.000 1.000 15093.690 15093.690 15093.690 15093.690 15093.690 0.006 0.004 0.003 89.843 62.890 44.922 15093.690 15093.690 15093.690 1.000 1.000 2.000 2.000 6.000 15093.690 15093.690 229418.080 229418.080 938827.360 0.012 0.008 0.018 1365.584 955.909 2794.129 214324.390 214324.390 407097.380 1.000 1.000 1.000 1.000 1.000 15093.690 15093.690 15093.690 15093.690 15093.690 0.006 0.004 0.003 89.843 62.890 44.922 15093.690 15093.690 15093.690
4322 374 TRANSFER 7466.120 C186075022 7466.120 0.000 C1001664465 0.000 0.000 1 0 C186075022_C1001664465 C186075022_TRANSFER C1001664465_TRANSFER C186075022_C1001664465_TRANSFER 15.000 1.000 1.000 1.000 1.000 1.000 7466.120 7466.120 7466.120 7466.120 7466.120 0.006 0.004 0.003 44.441 31.109 22.221 7466.120 7466.120 7466.120 1.000 1.000 1.000 1.000 1.000 7466.120 7466.120 7466.120 7466.120 7466.120 0.006 0.004 0.003 44.441 31.109 22.221 7466.120 7466.120 7466.120 1.000 1.000 1.000 1.000 1.000 7466.120 7466.120 7466.120 7466.120 7466.120 0.006 0.004 0.003 44.441 31.109 22.221 7466.120 7466.120 7466.120 1.000 1.000 1.000 1.000 1.000 7466.120 7466.120 7466.120 7466.120 7466.120 0.006 0.004 0.003 44.441 31.109 22.221 7466.120 7466.120 7466.120 1.000 1.000 1.000 1.000 1.000 7466.120 7466.120 7466.120 7466.120 7466.120 0.006 0.004 0.003 44.441 31.109 22.221 7466.120 7466.120 7466.120 1.000 1.000 1.000 1.000 1.000 7466.120 7466.120 7466.120 7466.120 7466.120 0.006 0.004 0.003 44.441 31.109 22.221 7466.120 7466.120 7466.120
4993 3 TRANSFER 22877.000 C1247938090 22877.000 0.000 C1002031672 0.000 0.000 1 0 C1247938090_C1002031672 C1247938090_TRANSFER C1002031672_TRANSFER C1247938090_C1002031672_TRANSFER 0.000 1.000 1.000 1.000 1.000 1.000 22877.000 22877.000 22877.000 22877.000 22877.000 0.333 0.333 0.333 7625.667 7625.667 7625.667 22877.000 22877.000 22877.000 1.000 1.000 1.000 1.000 1.000 22877.000 22877.000 22877.000 22877.000 22877.000 0.333 0.333 0.333 7625.667 7625.667 7625.667 22877.000 22877.000 22877.000 1.000 1.000 1.000 1.000 1.000 22877.000 22877.000 22877.000 22877.000 22877.000 0.333 0.333 0.333 7625.667 7625.667 7625.667 22877.000 22877.000 22877.000 1.000 1.000 1.000 1.000 1.000 22877.000 22877.000 22877.000 22877.000 22877.000 0.333 0.333 0.333 7625.667 7625.667 7625.667 22877.000 22877.000 22877.000 1.000 1.000 1.000 1.000 1.000 22877.000 22877.000 22877.000 22877.000 22877.000 0.333 0.333 0.333 7625.667 7625.667 7625.667 22877.000 22877.000 22877.000 1.000 1.000 1.000 1.000 1.000 22877.000 22877.000 22877.000 22877.000 22877.000 0.333 0.333 0.333 7625.667 7625.667 7625.667 22877.000 22877.000 22877.000
5311 635 TRANSFER 1363674.480 C1873557326 1363674.480 0.000 C1002151702 0.000 0.000 1 0 C1873557326_C1002151702 C1873557326_TRANSFER C1002151702_TRANSFER C1873557326_C1002151702_TRANSFER 26.000 1.000 1.000 1.000 1.000 1.000 1363674.480 1363674.480 1363674.480 1363674.480 1363674.480 0.006 0.004 0.003 8117.110 5681.977 4058.555 1363674.480 1363674.480 1363674.480 1.000 1.000 1.000 1.000 1.000 1363674.480 1363674.480 1363674.480 1363674.480 1363674.480 0.006 0.004 0.003 8117.110 5681.977 4058.555 1363674.480 1363674.480 1363674.480 1.000 1.000 1.000 1.000 1.000 1363674.480 1363674.480 1363674.480 1363674.480 1363674.480 0.006 0.004 0.003 8117.110 5681.977 4058.555 1363674.480 1363674.480 1363674.480 1.000 1.000 1.000 1.000 1.000 1363674.480 1363674.480 1363674.480 1363674.480 1363674.480 0.006 0.004 0.003 8117.110 5681.977 4058.555 1363674.480 1363674.480 1363674.480 1.000 1.000 1.000 1.000 1.000 1363674.480 1363674.480 1363674.480 1363674.480 1363674.480 0.006 0.004 0.003 8117.110 5681.977 4058.555 1363674.480 1363674.480 1363674.480 1.000 1.000 1.000 1.000 1.000 1363674.480 1363674.480 1363674.480 1363674.480 1363674.480 0.006 0.004 0.003 8117.110 5681.977 4058.555 1363674.480 1363674.480 1363674.480
5354 121 TRANSFER 2142164.000 C181177203 2142164.000 0.000 C1002183297 0.000 0.000 1 0 C181177203_C1002183297 C181177203_TRANSFER C1002183297_TRANSFER C181177203_C1002183297_TRANSFER 5.000 1.000 1.000 1.000 1.000 1.000 2142164.000 2142164.000 2142164.000 2142164.000 2142164.000 0.008 0.008 0.008 17703.835 17703.835 17703.835 2142164.000 2142164.000 2142164.000 1.000 1.000 1.000 1.000 1.000 2142164.000 2142164.000 2142164.000 2142164.000 2142164.000 0.008 0.008 0.008 17703.835 17703.835 17703.835 2142164.000 2142164.000 2142164.000 1.000 1.000 1.000 1.000 1.000 2142164.000 2142164.000 2142164.000 2142164.000 2142164.000 0.008 0.008 0.008 17703.835 17703.835 17703.835 2142164.000 2142164.000 2142164.000 1.000 1.000 1.000 1.000 1.000 2142164.000 2142164.000 2142164.000 2142164.000 2142164.000 0.008 0.008 0.008 17703.835 17703.835 17703.835 2142164.000 2142164.000 2142164.000 1.000 1.000 1.000 1.000 1.000 2142164.000 2142164.000 2142164.000 2142164.000 2142164.000 0.008 0.008 0.008 17703.835 17703.835 17703.835 2142164.000 2142164.000 2142164.000 1.000 1.000 1.000 1.000 1.000 2142164.000 2142164.000 2142164.000 2142164.000 2142164.000 0.008 0.008 0.008 17703.835 17703.835 17703.835 2142164.000 2142164.000 2142164.000
5489 562 TRANSFER 203881.960 C394205756 203881.960 0.000 C1002233012 0.000 0.000 1 0 C394205756_C1002233012 C394205756_TRANSFER C1002233012_TRANSFER C394205756_C1002233012_TRANSFER 23.000 1.000 1.000 1.000 1.000 1.000 203881.960 203881.960 203881.960 203881.960 203881.960 0.006 0.004 0.003 1213.583 849.508 606.792 203881.960 203881.960 203881.960 1.000 1.000 1.000 1.000 1.000 203881.960 203881.960 203881.960 203881.960 203881.960 0.006 0.004 0.003 1213.583 849.508 606.792 203881.960 203881.960 203881.960 1.000 1.000 1.000 1.000 1.000 203881.960 203881.960 203881.960 203881.960 203881.960 0.006 0.004 0.003 1213.583 849.508 606.792 203881.960 203881.960 203881.960 1.000 1.000 1.000 1.000 1.000 203881.960 203881.960 203881.960 203881.960 203881.960 0.006 0.004 0.003 1213.583 849.508 606.792 203881.960 203881.960 203881.960 1.000 1.000 1.000 1.000 1.000 203881.960 203881.960 203881.960 203881.960 203881.960 0.006 0.004 0.003 1213.583 849.508 606.792 203881.960 203881.960 203881.960 1.000 1.000 1.000 1.000 1.000 203881.960 203881.960 203881.960 203881.960 203881.960 0.006 0.004 0.003 1213.583 849.508 606.792 203881.960 203881.960 203881.960
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40021 696 CASH_OUT 803038.110 C2124823897 803038.110 0.000 C1017913693 10502128.900 11305167.010 1 0 C2124823897_C1017913693 C2124823897_CASH_OUT C1017913693_CASH_OUT C2124823897_C1017913693_CASH_OUT 29.000 1.000 1.000 1.000 1.000 1.000 803038.110 803038.110 803038.110 803038.110 803038.110 0.006 0.004 0.003 4779.989 3345.992 2389.994 803038.110 803038.110 803038.110 1.000 1.000 2.000 3.000 4.000 803038.110 803038.110 1534291.210 1625106.960 1702038.000 0.012 0.013 0.012 9132.686 6771.279 5065.589 803038.110 803038.110 803038.110 1.000 1.000 1.000 1.000 1.000 803038.110 803038.110 803038.110 803038.110 803038.110 0.006 0.004 0.003 4779.989 3345.992 2389.994 803038.110 803038.110 803038.110 1.000 1.000 1.000 1.000 1.000 803038.110 803038.110 803038.110 803038.110 803038.110 0.006 0.004 0.003 4779.989 3345.992 2389.994 803038.110 803038.110 803038.110 1.000 1.000 1.000 1.000 1.000 803038.110 803038.110 803038.110 803038.110 803038.110 0.006 0.004 0.003 4779.989 3345.992 2389.994 803038.110 803038.110 803038.110 1.000 1.000 1.000 1.000 1.000 803038.110 803038.110 803038.110 803038.110 803038.110 0.006 0.004 0.003 4779.989 3345.992 2389.994 803038.110 803038.110 803038.110
40475 526 CASH_OUT 377038.530 C774105103 377038.530 0.000 C1018085685 105508.480 482547.010 1 0 C774105103_C1018085685 C774105103_CASH_OUT C1018085685_CASH_OUT C774105103_C1018085685_CASH_OUT 21.000 1.000 1.000 1.000 1.000 1.000 377038.530 377038.530 377038.530 377038.530 377038.530 0.006 0.004 0.003 2244.277 1570.994 1122.138 377038.530 377038.530 377038.530 1.000 1.000 1.000 1.000 1.000 377038.530 377038.530 377038.530 377038.530 377038.530 0.006 0.004 0.003 2244.277 1570.994 1122.138 377038.530 377038.530 377038.530 1.000 1.000 1.000 1.000 1.000 377038.530 377038.530 377038.530 377038.530 377038.530 0.006 0.004 0.003 2244.277 1570.994 1122.138 377038.530 377038.530 377038.530 1.000 1.000 1.000 1.000 1.000 377038.530 377038.530 377038.530 377038.530 377038.530 0.006 0.004 0.003 2244.277 1570.994 1122.138 377038.530 377038.530 377038.530 1.000 1.000 1.000 1.000 1.000 377038.530 377038.530 377038.530 377038.530 377038.530 0.006 0.004 0.003 2244.277 1570.994 1122.138 377038.530 377038.530 377038.530 1.000 1.000 1.000 1.000 1.000 377038.530 377038.530 377038.530 377038.530 377038.530 0.006 0.004 0.003 2244.277 1570.994 1122.138 377038.530 377038.530 377038.530
40501 621 CASH_OUT 6961359.110 C1493356883 6961359.110 0.000 C1018094825 1734492.770 8695851.880 1 0 C1493356883_C1018094825 C1493356883_CASH_OUT C1018094825_CASH_OUT C1493356883_C1018094825_CASH_OUT 25.000 1.000 1.000 1.000 1.000 1.000 6961359.110 6961359.110 6961359.110 6961359.110 6961359.110 0.006 0.004 0.003 41436.661 29005.663 20718.331 6961359.110 6961359.110 6961359.110 1.000 1.000 1.000 3.000 7.000 6961359.110 6961359.110 6961359.110 7136646.980 7711533.490 0.006 0.013 0.021 41436.661 29736.029 22950.993 6961359.110 6961359.110 6961359.110 1.000 1.000 1.000 1.000 1.000 6961359.110 6961359.110 6961359.110 6961359.110 6961359.110 0.006 0.004 0.003 41436.661 29005.663 20718.331 6961359.110 6961359.110 6961359.110 1.000 1.000 1.000 1.000 1.000 6961359.110 6961359.110 6961359.110 6961359.110 6961359.110 0.006 0.004 0.003 41436.661 29005.663 20718.331 6961359.110 6961359.110 6961359.110 1.000 1.000 1.000 3.000 5.000 6961359.110 6961359.110 6961359.110 7136646.980 7320066.120 0.006 0.013 0.015 41436.661 29736.029 21785.911 6961359.110 6961359.110 6961359.110 1.000 1.000 1.000 1.000 1.000 6961359.110 6961359.110 6961359.110 6961359.110 6961359.110 0.006 0.004 0.003 41436.661 29005.663 20718.331 6961359.110 6961359.110 6961359.110
41029 164 CASH_OUT 175267.610 C979923889 175267.610 0.000 C1018310032 73374.370 248641.980 1 0 C979923889_C1018310032 C979923889_CASH_OUT C1018310032_CASH_OUT C979923889_C1018310032_CASH_OUT 6.000 1.000 1.000 1.000 1.000 1.000 175267.610 175267.610 175267.610 175267.610 175267.610 0.006 0.006 0.006 1068.705 1068.705 1068.705 175267.610 175267.610 175267.610 3.000 4.000 5.000 5.000 5.000 408164.850 558104.200 714436.450 714436.450 714436.450 0.030 0.030 0.030 4356.320 4356.320 4356.320 175267.610 175267.610 175267.610 1.000 1.000 1.000 1.000 1.000 175267.610 175267.610 175267.610 175267.610 175267.610 0.006 0.006 0.006 1068.705 1068.705 1068.705 175267.610 175267.610 175267.610 1.000 1.000 1.000 1.000 1.000 175267.610 175267.610 175267.610 175267.610 175267.610 0.006 0.006 0.006 1068.705 1068.705 1068.705 175267.610 175267.610 175267.610 1.000 2.000 3.000 3.000 3.000 175267.610 325206.960 481539.210 481539.210 481539.210 0.018 0.018 0.018 2936.215 2936.215 2936.215 175267.610 175267.610 175267.610 1.000 1.000 1.000 1.000 1.000 175267.610 175267.610 175267.610 175267.610 175267.610 0.006 0.006 0.006 1068.705 1068.705 1068.705 175267.610 175267.610 175267.610
41475 55 CASH_OUT 309254.050 C906689307 309254.050 0.000 C1018466821 218535.440 527789.500 1 0 C906689307_C1018466821 C906689307_CASH_OUT C1018466821_CASH_OUT C906689307_C1018466821_CASH_OUT 2.000 1.000 1.000 1.000 1.000 1.000 309254.050 309254.050 309254.050 309254.050 309254.050 0.018 0.018 0.018 5622.801 5622.801 5622.801 309254.050 309254.050 309254.050 1.000 1.000 1.000 1.000 1.000 309254.050 309254.050 309254.050 309254.050 309254.050 0.018 0.018 0.018 5622.801 5622.801 5622.801 309254.050 309254.050 309254.050 1.000 1.000 1.000 1.000 1.000 309254.050 309254.050 309254.050 309254.050 309254.050 0.018 0.018 0.018 5622.801 5622.801 5622.801 309254.050 309254.050 309254.050 1.000 1.000 1.000 1.000 1.000 309254.050 309254.050 309254.050 309254.050 309254.050 0.018 0.018 0.018 5622.801 5622.801 5622.801 309254.050 309254.050 309254.050 1.000 1.000 1.000 1.000 1.000 309254.050 309254.050 309254.050 309254.050 309254.050 0.018 0.018 0.018 5622.801 5622.801 5622.801 309254.050 309254.050 309254.050 1.000 1.000 1.000 1.000 1.000 309254.050 309254.050 309254.050 309254.050 309254.050 0.018 0.018 0.018 5622.801 5622.801 5622.801 309254.050 309254.050 309254.050
42643 71 CASH_OUT 322113.910 C1982559118 322113.910 0.000 C1018969803 0.000 322113.910 1 0 C1982559118_C1018969803 C1982559118_CASH_OUT C1018969803_CASH_OUT C1982559118_C1018969803_CASH_OUT 2.000 1.000 1.000 1.000 1.000 1.000 322113.910 322113.910 322113.910 322113.910 322113.910 0.014 0.014 0.014 4536.816 4536.816 4536.816 322113.910 322113.910 322113.910 1.000 2.000 2.000 2.000 2.000 322113.910 440980.790 440980.790 440980.790 440980.790 0.028 0.028 0.028 6210.997 6210.997 6210.997 322113.910 322113.910 322113.910 1.000 1.000 1.000 1.000 1.000 322113.910 322113.910 322113.910 322113.910 322113.910 0.014 0.014 0.014 4536.816 4536.816 4536.816 322113.910 322113.910 322113.910 1.000 1.000 1.000 1.000 1.000 322113.910 322113.910 322113.910 322113.910 322113.910 0.014 0.014 0.014 4536.816 4536.816 4536.816 322113.910 322113.910 322113.910 1.000 1.000 1.000 1.000 1.000 322113.910 322113.910 322113.910 322113.910 322113.910 0.014 0.014 0.014 4536.816 4536.816 4536.816 322113.910 322113.910 322113.910 1.000 1.000 1.000 1.000 1.000 322113.910 322113.910 322113.910 322113.910 322113.910 0.014 0.014 0.014 4536.816 4536.816 4536.816 322113.910 322113.910 322113.910
42918 111 CASH_OUT 574709.630 C132473843 574709.630 0.000 C101909578 0.000 574709.630 1 0 C132473843_C101909578 C132473843_CASH_OUT C101909578_CASH_OUT C132473843_C101909578_CASH_OUT 4.000 1.000 1.000 1.000 1.000 1.000 574709.630 574709.630 574709.630 574709.630 574709.630 0.009 0.009 0.009 5177.564 5177.564 5177.564 574709.630 574709.630 574709.630 1.000 1.000 1.000 1.000 1.000 574709.630 574709.630 574709.630 574709.630 574709.630 0.009 0.009 0.009 5177.564 5177.564 5177.564 574709.630 574709.630 574709.630 1.000 1.000 1.000 1.000 1.000 574709.630 574709.630 574709.630 574709.630 574709.630 0.009 0.009 0.009 5177.564 5177.564 5177.564 574709.630 574709.630 574709.630 1.000 1.000 1.000 1.000 1.000 574709.630 574709.630 574709.630 574709.630 574709.630 0.009 0.009 0.009 5177.564 5177.564 5177.564 574709.630 574709.630 574709.630 1.000 1.000 1.000 1.000 1.000 574709.630 574709.630 574709.630 574709.630 574709.630 0.009 0.009 0.009 5177.564 5177.564 5177.564 574709.630 574709.630 574709.630 1.000 1.000 1.000 1.000 1.000 574709.630 574709.630 574709.630 574709.630 574709.630 0.009 0.009 0.009 5177.564 5177.564 5177.564 574709.630 574709.630 574709.630
43241 421 TRANSFER 207021.450 C376689274 207021.450 0.000 C1019270751 0.000 0.000 1 0 C376689274_C1019270751 C376689274_TRANSFER C1019270751_TRANSFER C376689274_C1019270751_TRANSFER 17.000 1.000 1.000 1.000 1.000 1.000 207021.450 207021.450 207021.450 207021.450 207021.450 0.006 0.004 0.003 1232.271 862.589 616.135 207021.450 207021.450 207021.450 1.000 1.000 1.000 1.000 1.000 207021.450 207021.450 207021.450 207021.450 207021.450 0.006 0.004 0.003 1232.271 862.589 616.135 207021.450 207021.450 207021.450 1.000 1.000 1.000 1.000 1.000 207021.450 207021.450 207021.450 207021.450 207021.450 0.006 0.004 0.003 1232.271 862.589 616.135 207021.450 207021.450 207021.450 1.000 1.000 1.000 1.000 1.000 207021.450 207021.450 207021.450 207021.450 207021.450 0.006 0.004 0.003 1232.271 862.589 616.135 207021.450 207021.450 207021.450 1.000 1.000 1.000 1.000 1.000 207021.450 207021.450 207021.450 207021.450 207021.450 0.006 0.004 0.003 1232.271 862.589 616.135 207021.450 207021.450 207021.450 1.000 1.000 1.000 1.000 1.000 207021.450 207021.450 207021.450 207021.450 207021.450 0.006 0.004 0.003 1232.271 862.589 616.135 207021.450 207021.450 207021.450
44537 404 CASH_OUT 373322.870 C1753472917 373322.870 0.000 C101978061 112234.040 485556.910 1 0 C1753472917_C101978061 C1753472917_CASH_OUT C101978061_CASH_OUT C1753472917_C101978061_CASH_OUT 16.000 1.000 1.000 1.000 1.000 1.000 373322.870 373322.870 373322.870 373322.870 373322.870 0.006 0.004 0.003 2222.160 1555.512 1111.080 373322.870 373322.870 373322.870 1.000 1.000 2.000 2.000 2.000 373322.870 373322.870 485556.910 485556.910 485556.910 0.012 0.008 0.006 2890.220 2023.154 1445.110 373322.870 373322.870 373322.870 1.000 1.000 1.000 1.000 1.000 373322.870 373322.870 373322.870 373322.870 373322.870 0.006 0.004 0.003 2222.160 1555.512 1111.080 373322.870 373322.870 373322.870 1.000 1.000 1.000 1.000 1.000 373322.870 373322.870 373322.870 373322.870 373322.870 0.006 0.004 0.003 2222.160 1555.512 1111.080 373322.870 373322.870 373322.870 1.000 1.000 2.000 2.000 2.000 373322.870 373322.870 485556.910 485556.910 485556.910 0.012 0.008 0.006 2890.220 2023.154 1445.110 373322.870 373322.870 373322.870 1.000 1.000 1.000 1.000 1.000 373322.870 373322.870 373322.870 373322.870 373322.870 0.006 0.004 0.003 2222.160 1555.512 1111.080 373322.870 373322.870 373322.870
46865 149 CASH_OUT 29832.810 C185736530 29832.810 0.000 C1020879076 82642.620 112475.430 1 0 C185736530_C1020879076 C185736530_CASH_OUT C1020879076_CASH_OUT C185736530_C1020879076_CASH_OUT 6.000 1.000 1.000 1.000 1.000 1.000 29832.810 29832.810 29832.810 29832.810 29832.810 0.007 0.007 0.007 200.220 200.220 200.220 29832.810 29832.810 29832.810 2.000 2.000 2.000 2.000 2.000 112475.430 112475.430 112475.430 112475.430 112475.430 0.013 0.013 0.013 754.869 754.869 754.869 82642.620 82642.620 82642.620 1.000 1.000 1.000 1.000 1.000 29832.810 29832.810 29832.810 29832.810 29832.810 0.007 0.007 0.007 200.220 200.220 200.220 29832.810 29832.810 29832.810 1.000 1.000 1.000 1.000 1.000 29832.810 29832.810 29832.810 29832.810 29832.810 0.007 0.007 0.007 200.220 200.220 200.220 29832.810 29832.810 29832.810 2.000 2.000 2.000 2.000 2.000 112475.430 112475.430 112475.430 112475.430 112475.430 0.013 0.013 0.013 754.869 754.869 754.869 82642.620 82642.620 82642.620 1.000 1.000 1.000 1.000 1.000 29832.810 29832.810 29832.810 29832.810 29832.810 0.007 0.007 0.007 200.220 200.220 200.220 29832.810 29832.810 29832.810
47220 387 CASH_OUT 20920.390 C18423061 20920.390 0.000 C1021087479 359472.940 380393.330 1 0 C18423061_C1021087479 C18423061_CASH_OUT C1021087479_CASH_OUT C18423061_C1021087479_CASH_OUT 16.000 1.000 1.000 1.000 1.000 1.000 20920.390 20920.390 20920.390 20920.390 20920.390 0.006 0.004 0.003 124.526 87.168 62.263 20920.390 20920.390 20920.390 3.000 3.000 4.000 4.000 4.000 368569.140 368569.140 467405.640 467405.640 467405.640 0.024 0.017 0.012 2782.176 1947.524 1391.088 203890.980 203890.980 203890.980 1.000 1.000 1.000 1.000 1.000 20920.390 20920.390 20920.390 20920.390 20920.390 0.006 0.004 0.003 124.526 87.168 62.263 20920.390 20920.390 20920.390 1.000 1.000 1.000 1.000 1.000 20920.390 20920.390 20920.390 20920.390 20920.390 0.006 0.004 0.003 124.526 87.168 62.263 20920.390 20920.390 20920.390 3.000 3.000 3.000 3.000 3.000 368569.140 368569.140 368569.140 368569.140 368569.140 0.018 0.013 0.009 2193.864 1535.705 1096.932 203890.980 203890.980 203890.980 1.000 1.000 1.000 1.000 1.000 20920.390 20920.390 20920.390 20920.390 20920.390 0.006 0.004 0.003 124.526 87.168 62.263 20920.390 20920.390 20920.390
47883 66 CASH_OUT 107188.410 C2059976574 107188.410 0.000 C1021456304 696135.430 803323.830 1 0 C2059976574_C1021456304 C2059976574_CASH_OUT C1021456304_CASH_OUT C2059976574_C1021456304_CASH_OUT 2.000 1.000 1.000 1.000 1.000 1.000 107188.410 107188.410 107188.410 107188.410 107188.410 0.015 0.015 0.015 1624.067 1624.067 1624.067 107188.410 107188.410 107188.410 2.000 5.000 5.000 5.000 5.000 269113.220 1008942.020 1008942.020 1008942.020 1008942.020 0.076 0.076 0.076 15287.000 15287.000 15287.000 448598.870 448598.870 448598.870 1.000 1.000 1.000 1.000 1.000 107188.410 107188.410 107188.410 107188.410 107188.410 0.015 0.015 0.015 1624.067 1624.067 1624.067 107188.410 107188.410 107188.410 1.000 1.000 1.000 1.000 1.000 107188.410 107188.410 107188.410 107188.410 107188.410 0.015 0.015 0.015 1624.067 1624.067 1624.067 107188.410 107188.410 107188.410 2.000 3.000 3.000 3.000 3.000 269113.220 315202.500 315202.500 315202.500 315202.500 0.045 0.045 0.045 4775.795 4775.795 4775.795 161924.810 161924.810 161924.810 1.000 1.000 1.000 1.000 1.000 107188.410 107188.410 107188.410 107188.410 107188.410 0.015 0.015 0.015 1624.067 1624.067 1624.067 107188.410 107188.410 107188.410

4.3 Time since features¶

In [32]:
for i in ['nameOrig','nameDest','nameOrig_nameDest','nameOrig_type','nameDest_type','nameOrig_nameDest_type']:
    #print(i)
    #print(i + '_' + 'time_since_last_txn')
    aml_data = aml_data.sort_values(by = [i,'step']).reset_index(drop=True)
    aml_data[i + '_' + 'time_since_last_txn'] = aml_data['step'] - aml_data.groupby([i])['step'].shift(1)
In [33]:
aml_data.tail()
Out[33]:
step type amount nameOrig oldbalanceOrg newbalanceOrig nameDest oldbalanceDest newbalanceDest isFraud isFlaggedFraud nameOrig_nameDest nameOrig_type nameDest_type nameOrig_nameDest_type day nameOrig_rolling_txn_count_1day nameOrig_rolling_txn_count_3day nameOrig_rolling_txn_count_7day nameOrig_rolling_txn_count_10day nameOrig_rolling_txn_count_14day nameOrig_rolling_txn_sum_1day nameOrig_rolling_txn_sum_3day nameOrig_rolling_txn_sum_7day nameOrig_rolling_txn_sum_10day nameOrig_rolling_txn_sum_14day nameOrig_rolling_txn_count_mean_7day nameOrig_rolling_txn_count_mean_10day nameOrig_rolling_txn_count_mean_14day nameOrig_rolling_txn_amount_mean_7day nameOrig_rolling_txn_amount_mean_10day nameOrig_rolling_txn_amount_mean_14day nameOrig_rolling_txn_amount_max_7day nameOrig_rolling_txn_amount_max_10day nameOrig_rolling_txn_amount_max_14day nameDest_rolling_txn_count_1day nameDest_rolling_txn_count_3day nameDest_rolling_txn_count_7day nameDest_rolling_txn_count_10day nameDest_rolling_txn_count_14day nameDest_rolling_txn_sum_1day nameDest_rolling_txn_sum_3day nameDest_rolling_txn_sum_7day nameDest_rolling_txn_sum_10day nameDest_rolling_txn_sum_14day nameDest_rolling_txn_count_mean_7day nameDest_rolling_txn_count_mean_10day nameDest_rolling_txn_count_mean_14day nameDest_rolling_txn_amount_mean_7day nameDest_rolling_txn_amount_mean_10day nameDest_rolling_txn_amount_mean_14day nameDest_rolling_txn_amount_max_7day nameDest_rolling_txn_amount_max_10day nameDest_rolling_txn_amount_max_14day nameOrig_nameDest_rolling_txn_count_1day nameOrig_nameDest_rolling_txn_count_3day nameOrig_nameDest_rolling_txn_count_7day nameOrig_nameDest_rolling_txn_count_10day nameOrig_nameDest_rolling_txn_count_14day nameOrig_nameDest_rolling_txn_sum_1day nameOrig_nameDest_rolling_txn_sum_3day nameOrig_nameDest_rolling_txn_sum_7day nameOrig_nameDest_rolling_txn_sum_10day nameOrig_nameDest_rolling_txn_sum_14day nameOrig_nameDest_rolling_txn_count_mean_7day nameOrig_nameDest_rolling_txn_count_mean_10day nameOrig_nameDest_rolling_txn_count_mean_14day nameOrig_nameDest_rolling_txn_amount_mean_7day nameOrig_nameDest_rolling_txn_amount_mean_10day nameOrig_nameDest_rolling_txn_amount_mean_14day nameOrig_nameDest_rolling_txn_amount_max_7day nameOrig_nameDest_rolling_txn_amount_max_10day nameOrig_nameDest_rolling_txn_amount_max_14day nameOrig_type_rolling_txn_count_1day nameOrig_type_rolling_txn_count_3day nameOrig_type_rolling_txn_count_7day nameOrig_type_rolling_txn_count_10day nameOrig_type_rolling_txn_count_14day nameOrig_type_rolling_txn_sum_1day nameOrig_type_rolling_txn_sum_3day nameOrig_type_rolling_txn_sum_7day nameOrig_type_rolling_txn_sum_10day nameOrig_type_rolling_txn_sum_14day nameOrig_type_rolling_txn_count_mean_7day nameOrig_type_rolling_txn_count_mean_10day nameOrig_type_rolling_txn_count_mean_14day nameOrig_type_rolling_txn_amount_mean_7day nameOrig_type_rolling_txn_amount_mean_10day nameOrig_type_rolling_txn_amount_mean_14day nameOrig_type_rolling_txn_amount_max_7day nameOrig_type_rolling_txn_amount_max_10day nameOrig_type_rolling_txn_amount_max_14day nameDest_type_rolling_txn_count_1day nameDest_type_rolling_txn_count_3day nameDest_type_rolling_txn_count_7day nameDest_type_rolling_txn_count_10day nameDest_type_rolling_txn_count_14day nameDest_type_rolling_txn_sum_1day nameDest_type_rolling_txn_sum_3day nameDest_type_rolling_txn_sum_7day nameDest_type_rolling_txn_sum_10day nameDest_type_rolling_txn_sum_14day nameDest_type_rolling_txn_count_mean_7day nameDest_type_rolling_txn_count_mean_10day nameDest_type_rolling_txn_count_mean_14day nameDest_type_rolling_txn_amount_mean_7day nameDest_type_rolling_txn_amount_mean_10day nameDest_type_rolling_txn_amount_mean_14day nameDest_type_rolling_txn_amount_max_7day nameDest_type_rolling_txn_amount_max_10day nameDest_type_rolling_txn_amount_max_14day nameOrig_nameDest_type_rolling_txn_count_1day nameOrig_nameDest_type_rolling_txn_count_3day nameOrig_nameDest_type_rolling_txn_count_7day nameOrig_nameDest_type_rolling_txn_count_10day nameOrig_nameDest_type_rolling_txn_count_14day nameOrig_nameDest_type_rolling_txn_sum_1day nameOrig_nameDest_type_rolling_txn_sum_3day nameOrig_nameDest_type_rolling_txn_sum_7day nameOrig_nameDest_type_rolling_txn_sum_10day nameOrig_nameDest_type_rolling_txn_sum_14day nameOrig_nameDest_type_rolling_txn_count_mean_7day nameOrig_nameDest_type_rolling_txn_count_mean_10day nameOrig_nameDest_type_rolling_txn_count_mean_14day nameOrig_nameDest_type_rolling_txn_amount_mean_7day nameOrig_nameDest_type_rolling_txn_amount_mean_10day nameOrig_nameDest_type_rolling_txn_amount_mean_14day nameOrig_nameDest_type_rolling_txn_amount_max_7day nameOrig_nameDest_type_rolling_txn_amount_max_10day nameOrig_nameDest_type_rolling_txn_amount_max_14day nameOrig_time_since_last_txn nameDest_time_since_last_txn nameOrig_nameDest_time_since_last_txn nameOrig_type_time_since_last_txn nameDest_type_time_since_last_txn nameOrig_nameDest_type_time_since_last_txn
99995 38 CASH_OUT 297007.040 C999861388 277835.000 0.000 C1021741245 1361116.410 1658123.450 0 0 C999861388_C1021741245 C999861388_CASH_OUT C1021741245_CASH_OUT C999861388_C1021741245_CASH_OUT 1.000 1.000 1.000 1.000 1.000 1.000 297007.040 297007.040 297007.040 297007.040 297007.040 0.026 0.026 0.026 7815.975 7815.975 7815.975 297007.040 297007.040 297007.040 11.000 18.000 18.000 18.000 18.000 1873990.530 3714646.190 3714646.190 3714646.190 3714646.190 0.474 0.474 0.474 97753.847 97753.847 97753.847 890723.890 890723.890 890723.890 1.000 1.000 1.000 1.000 1.000 297007.040 297007.040 297007.040 297007.040 297007.040 0.026 0.026 0.026 7815.975 7815.975 7815.975 297007.040 297007.040 297007.040 1.000 1.000 1.000 1.000 1.000 297007.040 297007.040 297007.040 297007.040 297007.040 0.026 0.026 0.026 7815.975 7815.975 7815.975 297007.040 297007.040 297007.040 6.000 9.000 9.000 9.000 9.000 1285131.070 2095968.210 2095968.210 2095968.210 2095968.210 0.237 0.237 0.237 55157.058 55157.058 55157.058 527560.770 527560.770 527560.770 1.000 1.000 1.000 1.000 1.000 297007.040 297007.040 297007.040 297007.040 297007.040 0.026 0.026 0.026 7815.975 7815.975 7815.975 297007.040 297007.040 297007.040 NaN 0.000 NaN NaN 0.000 NaN
99996 35 CASH_OUT 214230.510 C999867084 9519.000 0.000 C1018629838 893383.070 1107613.580 0 0 C999867084_C1018629838 C999867084_CASH_OUT C1018629838_CASH_OUT C999867084_C1018629838_CASH_OUT 1.000 1.000 1.000 1.000 1.000 1.000 214230.510 214230.510 214230.510 214230.510 214230.510 0.029 0.029 0.029 6120.872 6120.872 6120.872 214230.510 214230.510 214230.510 8.000 8.000 8.000 8.000 8.000 1531378.000 1531378.000 1531378.000 1531378.000 1531378.000 0.229 0.229 0.229 43753.657 43753.657 43753.657 548506.740 548506.740 548506.740 1.000 1.000 1.000 1.000 1.000 214230.510 214230.510 214230.510 214230.510 214230.510 0.029 0.029 0.029 6120.872 6120.872 6120.872 214230.510 214230.510 214230.510 1.000 1.000 1.000 1.000 1.000 214230.510 214230.510 214230.510 214230.510 214230.510 0.029 0.029 0.029 6120.872 6120.872 6120.872 214230.510 214230.510 214230.510 6.000 6.000 6.000 6.000 6.000 1043191.920 1043191.920 1043191.920 1043191.920 1043191.920 0.171 0.171 0.171 29805.483 29805.483 29805.483 548506.740 548506.740 548506.740 1.000 1.000 1.000 1.000 1.000 214230.510 214230.510 214230.510 214230.510 214230.510 0.029 0.029 0.029 6120.872 6120.872 6120.872 214230.510 214230.510 214230.510 NaN 0.000 NaN NaN 0.000 NaN
99997 253 CASH_OUT 143021.030 C999881658 10144.000 0.000 C1017189714 122152.630 265173.650 0 0 C999881658_C1017189714 C999881658_CASH_OUT C1017189714_CASH_OUT C999881658_C1017189714_CASH_OUT 10.000 1.000 1.000 1.000 1.000 1.000 143021.030 143021.030 143021.030 143021.030 143021.030 0.006 0.004 0.004 851.316 595.921 565.301 143021.030 143021.030 143021.030 4.000 5.000 5.000 5.000 5.000 463735.770 800491.580 800491.580 800491.580 800491.580 0.030 0.021 0.020 4764.831 3335.382 3163.998 336755.810 336755.810 336755.810 1.000 1.000 1.000 1.000 1.000 143021.030 143021.030 143021.030 143021.030 143021.030 0.006 0.004 0.004 851.316 595.921 565.301 143021.030 143021.030 143021.030 1.000 1.000 1.000 1.000 1.000 143021.030 143021.030 143021.030 143021.030 143021.030 0.006 0.004 0.004 851.316 595.921 565.301 143021.030 143021.030 143021.030 2.000 3.000 3.000 3.000 3.000 196076.810 532832.620 532832.620 532832.620 532832.620 0.018 0.013 0.012 3171.623 2220.136 2106.058 336755.810 336755.810 336755.810 1.000 1.000 1.000 1.000 1.000 143021.030 143021.030 143021.030 143021.030 143021.030 0.006 0.004 0.004 851.316 595.921 565.301 143021.030 143021.030 143021.030 NaN 1.000 NaN NaN 2.000 NaN
99998 164 CASH_OUT 176315.260 C999960842 21363.000 0.000 C1018338551 0.000 176315.260 0 0 C999960842_C1018338551 C999960842_CASH_OUT C1018338551_CASH_OUT C999960842_C1018338551_CASH_OUT 6.000 1.000 1.000 1.000 1.000 1.000 176315.260 176315.260 176315.260 176315.260 176315.260 0.006 0.006 0.006 1075.093 1075.093 1075.093 176315.260 176315.260 176315.260 2.000 2.000 3.000 3.000 3.000 346429.580 346429.580 527469.440 527469.440 527469.440 0.018 0.018 0.018 3216.277 3216.277 3216.277 181039.860 181039.860 181039.860 1.000 1.000 1.000 1.000 1.000 176315.260 176315.260 176315.260 176315.260 176315.260 0.006 0.006 0.006 1075.093 1075.093 1075.093 176315.260 176315.260 176315.260 1.000 1.000 1.000 1.000 1.000 176315.260 176315.260 176315.260 176315.260 176315.260 0.006 0.006 0.006 1075.093 1075.093 1075.093 176315.260 176315.260 176315.260 1.000 1.000 1.000 1.000 1.000 176315.260 176315.260 176315.260 176315.260 176315.260 0.006 0.006 0.006 1075.093 1075.093 1075.093 176315.260 176315.260 176315.260 1.000 1.000 1.000 1.000 1.000 176315.260 176315.260 176315.260 176315.260 176315.260 0.006 0.006 0.006 1075.093 1075.093 1075.093 176315.260 176315.260 176315.260 NaN 9.000 NaN NaN NaN NaN
99999 42 TRANSFER 901542.090 C999989921 3181.000 0.000 C1002057348 0.000 901542.090 0 0 C999989921_C1002057348 C999989921_TRANSFER C1002057348_TRANSFER C999989921_C1002057348_TRANSFER 1.000 1.000 1.000 1.000 1.000 1.000 901542.090 901542.090 901542.090 901542.090 901542.090 0.024 0.024 0.024 21465.288 21465.288 21465.288 901542.090 901542.090 901542.090 1.000 1.000 1.000 1.000 1.000 901542.090 901542.090 901542.090 901542.090 901542.090 0.024 0.024 0.024 21465.288 21465.288 21465.288 901542.090 901542.090 901542.090 1.000 1.000 1.000 1.000 1.000 901542.090 901542.090 901542.090 901542.090 901542.090 0.024 0.024 0.024 21465.288 21465.288 21465.288 901542.090 901542.090 901542.090 1.000 1.000 1.000 1.000 1.000 901542.090 901542.090 901542.090 901542.090 901542.090 0.024 0.024 0.024 21465.288 21465.288 21465.288 901542.090 901542.090 901542.090 1.000 1.000 1.000 1.000 1.000 901542.090 901542.090 901542.090 901542.090 901542.090 0.024 0.024 0.024 21465.288 21465.288 21465.288 901542.090 901542.090 901542.090 1.000 1.000 1.000 1.000 1.000 901542.090 901542.090 901542.090 901542.090 901542.090 0.024 0.024 0.024 21465.288 21465.288 21465.288 901542.090 901542.090 901542.090 NaN NaN NaN NaN NaN NaN
In [34]:
#aml_data[aml_data.nameDest == 'C1018629838'].tail()
In [35]:
#aml_data[aml_data.nameDest == 'C1017189714'].sort_values(by = ['nameDest_type','step']).reset_index(drop=True)
aml_data[aml_data.nameDest == 'C104038589'].sort_values(by = ['nameDest','step']).reset_index(drop=True)
Out[35]:
step type amount nameOrig oldbalanceOrg newbalanceOrig nameDest oldbalanceDest newbalanceDest isFraud isFlaggedFraud nameOrig_nameDest nameOrig_type nameDest_type nameOrig_nameDest_type day nameOrig_rolling_txn_count_1day nameOrig_rolling_txn_count_3day nameOrig_rolling_txn_count_7day nameOrig_rolling_txn_count_10day nameOrig_rolling_txn_count_14day nameOrig_rolling_txn_sum_1day nameOrig_rolling_txn_sum_3day nameOrig_rolling_txn_sum_7day nameOrig_rolling_txn_sum_10day nameOrig_rolling_txn_sum_14day nameOrig_rolling_txn_count_mean_7day nameOrig_rolling_txn_count_mean_10day nameOrig_rolling_txn_count_mean_14day nameOrig_rolling_txn_amount_mean_7day nameOrig_rolling_txn_amount_mean_10day nameOrig_rolling_txn_amount_mean_14day nameOrig_rolling_txn_amount_max_7day nameOrig_rolling_txn_amount_max_10day nameOrig_rolling_txn_amount_max_14day nameDest_rolling_txn_count_1day nameDest_rolling_txn_count_3day nameDest_rolling_txn_count_7day nameDest_rolling_txn_count_10day nameDest_rolling_txn_count_14day nameDest_rolling_txn_sum_1day nameDest_rolling_txn_sum_3day nameDest_rolling_txn_sum_7day nameDest_rolling_txn_sum_10day nameDest_rolling_txn_sum_14day nameDest_rolling_txn_count_mean_7day nameDest_rolling_txn_count_mean_10day nameDest_rolling_txn_count_mean_14day nameDest_rolling_txn_amount_mean_7day nameDest_rolling_txn_amount_mean_10day nameDest_rolling_txn_amount_mean_14day nameDest_rolling_txn_amount_max_7day nameDest_rolling_txn_amount_max_10day nameDest_rolling_txn_amount_max_14day nameOrig_nameDest_rolling_txn_count_1day nameOrig_nameDest_rolling_txn_count_3day nameOrig_nameDest_rolling_txn_count_7day nameOrig_nameDest_rolling_txn_count_10day nameOrig_nameDest_rolling_txn_count_14day nameOrig_nameDest_rolling_txn_sum_1day nameOrig_nameDest_rolling_txn_sum_3day nameOrig_nameDest_rolling_txn_sum_7day nameOrig_nameDest_rolling_txn_sum_10day nameOrig_nameDest_rolling_txn_sum_14day nameOrig_nameDest_rolling_txn_count_mean_7day nameOrig_nameDest_rolling_txn_count_mean_10day nameOrig_nameDest_rolling_txn_count_mean_14day nameOrig_nameDest_rolling_txn_amount_mean_7day nameOrig_nameDest_rolling_txn_amount_mean_10day nameOrig_nameDest_rolling_txn_amount_mean_14day nameOrig_nameDest_rolling_txn_amount_max_7day nameOrig_nameDest_rolling_txn_amount_max_10day nameOrig_nameDest_rolling_txn_amount_max_14day nameOrig_type_rolling_txn_count_1day nameOrig_type_rolling_txn_count_3day nameOrig_type_rolling_txn_count_7day nameOrig_type_rolling_txn_count_10day nameOrig_type_rolling_txn_count_14day nameOrig_type_rolling_txn_sum_1day nameOrig_type_rolling_txn_sum_3day nameOrig_type_rolling_txn_sum_7day nameOrig_type_rolling_txn_sum_10day nameOrig_type_rolling_txn_sum_14day nameOrig_type_rolling_txn_count_mean_7day nameOrig_type_rolling_txn_count_mean_10day nameOrig_type_rolling_txn_count_mean_14day nameOrig_type_rolling_txn_amount_mean_7day nameOrig_type_rolling_txn_amount_mean_10day nameOrig_type_rolling_txn_amount_mean_14day nameOrig_type_rolling_txn_amount_max_7day nameOrig_type_rolling_txn_amount_max_10day nameOrig_type_rolling_txn_amount_max_14day nameDest_type_rolling_txn_count_1day nameDest_type_rolling_txn_count_3day nameDest_type_rolling_txn_count_7day nameDest_type_rolling_txn_count_10day nameDest_type_rolling_txn_count_14day nameDest_type_rolling_txn_sum_1day nameDest_type_rolling_txn_sum_3day nameDest_type_rolling_txn_sum_7day nameDest_type_rolling_txn_sum_10day nameDest_type_rolling_txn_sum_14day nameDest_type_rolling_txn_count_mean_7day nameDest_type_rolling_txn_count_mean_10day nameDest_type_rolling_txn_count_mean_14day nameDest_type_rolling_txn_amount_mean_7day nameDest_type_rolling_txn_amount_mean_10day nameDest_type_rolling_txn_amount_mean_14day nameDest_type_rolling_txn_amount_max_7day nameDest_type_rolling_txn_amount_max_10day nameDest_type_rolling_txn_amount_max_14day nameOrig_nameDest_type_rolling_txn_count_1day nameOrig_nameDest_type_rolling_txn_count_3day nameOrig_nameDest_type_rolling_txn_count_7day nameOrig_nameDest_type_rolling_txn_count_10day nameOrig_nameDest_type_rolling_txn_count_14day nameOrig_nameDest_type_rolling_txn_sum_1day nameOrig_nameDest_type_rolling_txn_sum_3day nameOrig_nameDest_type_rolling_txn_sum_7day nameOrig_nameDest_type_rolling_txn_sum_10day nameOrig_nameDest_type_rolling_txn_sum_14day nameOrig_nameDest_type_rolling_txn_count_mean_7day nameOrig_nameDest_type_rolling_txn_count_mean_10day nameOrig_nameDest_type_rolling_txn_count_mean_14day nameOrig_nameDest_type_rolling_txn_amount_mean_7day nameOrig_nameDest_type_rolling_txn_amount_mean_10day nameOrig_nameDest_type_rolling_txn_amount_mean_14day nameOrig_nameDest_type_rolling_txn_amount_max_7day nameOrig_nameDest_type_rolling_txn_amount_max_10day nameOrig_nameDest_type_rolling_txn_amount_max_14day nameOrig_time_since_last_txn nameDest_time_since_last_txn nameOrig_nameDest_time_since_last_txn nameOrig_type_time_since_last_txn nameDest_type_time_since_last_txn nameOrig_nameDest_type_time_since_last_txn
0 39 TRANSFER 152042.160 C1118399210 152042.160 0.000 C104038589 0.000 0.000 1 0 C1118399210_C104038589 C1118399210_TRANSFER C104038589_TRANSFER C1118399210_C104038589_TRANSFER 1.000 1.000 1.000 1.000 1.000 1.000 152042.160 152042.160 152042.160 152042.160 152042.160 0.026 0.026 0.026 3898.517 3898.517 3898.517 152042.160 152042.160 152042.160 1.000 1.000 1.000 1.000 1.000 152042.160 152042.160 152042.160 152042.160 152042.160 0.026 0.026 0.026 3898.517 3898.517 3898.517 152042.160 152042.160 152042.160 1.000 1.000 1.000 1.000 1.000 152042.160 152042.160 152042.160 152042.160 152042.160 0.026 0.026 0.026 3898.517 3898.517 3898.517 152042.160 152042.160 152042.160 1.000 1.000 1.000 1.000 1.000 152042.160 152042.160 152042.160 152042.160 152042.160 0.026 0.026 0.026 3898.517 3898.517 3898.517 152042.160 152042.160 152042.160 1.000 1.000 1.000 1.000 1.000 152042.160 152042.160 152042.160 152042.160 152042.160 0.026 0.026 0.026 3898.517 3898.517 3898.517 152042.160 152042.160 152042.160 1.000 1.000 1.000 1.000 1.000 152042.160 152042.160 152042.160 152042.160 152042.160 0.026 0.026 0.026 3898.517 3898.517 3898.517 152042.160 152042.160 152042.160 NaN NaN NaN NaN NaN NaN
1 41 CASH_IN 297124.850 C1422936279 10435.000 307559.850 C104038589 0.000 0.000 0 0 C1422936279_C104038589 C1422936279_CASH_IN C104038589_CASH_IN C1422936279_C104038589_CASH_IN 1.000 1.000 1.000 1.000 1.000 1.000 297124.850 297124.850 297124.850 297124.850 297124.850 0.024 0.024 0.024 7246.948 7246.948 7246.948 297124.850 297124.850 297124.850 2.000 2.000 2.000 2.000 2.000 449167.010 449167.010 449167.010 449167.010 449167.010 0.049 0.049 0.049 10955.293 10955.293 10955.293 297124.850 297124.850 297124.850 1.000 1.000 1.000 1.000 1.000 297124.850 297124.850 297124.850 297124.850 297124.850 0.024 0.024 0.024 7246.948 7246.948 7246.948 297124.850 297124.850 297124.850 1.000 1.000 1.000 1.000 1.000 297124.850 297124.850 297124.850 297124.850 297124.850 0.024 0.024 0.024 7246.948 7246.948 7246.948 297124.850 297124.850 297124.850 1.000 1.000 1.000 1.000 1.000 297124.850 297124.850 297124.850 297124.850 297124.850 0.024 0.024 0.024 7246.948 7246.948 7246.948 297124.850 297124.850 297124.850 1.000 1.000 1.000 1.000 1.000 297124.850 297124.850 297124.850 297124.850 297124.850 0.024 0.024 0.024 7246.948 7246.948 7246.948 297124.850 297124.850 297124.850 NaN 2.000 NaN NaN NaN NaN
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13 190 CASH_OUT 40820.930 C1758389668 0.000 0.000 C104038589 2344701.050 2385521.980 0 0 C1758389668_C104038589 C1758389668_CASH_OUT C104038589_CASH_OUT C1758389668_C104038589_CASH_OUT 7.000 1.000 1.000 1.000 1.000 1.000 40820.930 40820.930 40820.930 40820.930 40820.930 0.006 0.005 0.005 242.982 214.847 214.847 40820.930 40820.930 40820.930 3.000 11.000 14.000 14.000 14.000 495492.110 2873595.620 5373490.440 5373490.440 5373490.440 0.083 0.074 0.074 31985.062 28281.529 28281.529 2050727.810 2050727.810 2050727.810 1.000 1.000 1.000 1.000 1.000 40820.930 40820.930 40820.930 40820.930 40820.930 0.006 0.005 0.005 242.982 214.847 214.847 40820.930 40820.930 40820.930 1.000 1.000 1.000 1.000 1.000 40820.930 40820.930 40820.930 40820.930 40820.930 0.006 0.005 0.005 242.982 214.847 214.847 40820.930 40820.930 40820.930 1.000 4.000 5.000 5.000 5.000 40820.930 482863.200 2533591.010 2533591.010 2533591.010 0.030 0.026 0.026 15080.899 13334.690 13334.690 2050727.810 2050727.810 2050727.810 1.000 1.000 1.000 1.000 1.000 40820.930 40820.930 40820.930 40820.930 40820.930 0.006 0.005 0.005 242.982 214.847 214.847 40820.930 40820.930 40820.930 NaN 7.000 NaN NaN 29.000 NaN
14 228 CASH_OUT 305133.630 C1699312181 0.000 0.000 C104038589 2385521.980 2690655.620 0 0 C1699312181_C104038589 C1699312181_CASH_OUT C104038589_CASH_OUT C1699312181_C104038589_CASH_OUT 9.000 1.000 1.000 1.000 1.000 1.000 305133.630 305133.630 305133.630 305133.630 305133.630 0.006 0.004 0.004 1816.272 1338.305 1338.305 305133.630 305133.630 305133.630 1.000 8.000 12.000 15.000 15.000 305133.630 1864116.870 3178729.250 5678624.070 5678624.070 0.071 0.066 0.066 18921.007 24906.246 24906.246 662038.200 2050727.810 2050727.810 1.000 1.000 1.000 1.000 1.000 305133.630 305133.630 305133.630 305133.630 305133.630 0.006 0.004 0.004 1816.272 1338.305 1338.305 305133.630 305133.630 305133.630 1.000 1.000 1.000 1.000 1.000 305133.630 305133.630 305133.630 305133.630 305133.630 0.006 0.004 0.004 1816.272 1338.305 1338.305 305133.630 305133.630 305133.630 1.000 4.000 5.000 6.000 6.000 305133.630 741175.740 787996.830 2838724.640 2838724.640 0.030 0.026 0.026 4690.457 12450.547 12450.547 305133.630 2050727.810 2050727.810 1.000 1.000 1.000 1.000 1.000 305133.630 305133.630 305133.630 305133.630 305133.630 0.006 0.004 0.004 1816.272 1338.305 1338.305 305133.630 305133.630 305133.630 NaN 38.000 NaN NaN 38.000 NaN
15 254 CASH_OUT 219043.060 C214233519 187883.000 0.000 C104038589 2690655.620 2909698.670 0 0 C214233519_C104038589 C214233519_CASH_OUT C104038589_CASH_OUT C214233519_C104038589_CASH_OUT 10.000 1.000 1.000 1.000 1.000 1.000 219043.060 219043.060 219043.060 219043.060 219043.060 0.006 0.004 0.004 1303.828 912.679 862.374 219043.060 219043.060 219043.060 1.000 4.000 13.000 16.000 16.000 219043.060 707991.800 3397772.310 5897667.130 5897667.130 0.077 0.067 0.063 20224.835 24573.613 23219.162 662038.200 2050727.810 2050727.810 1.000 1.000 1.000 1.000 1.000 219043.060 219043.060 219043.060 219043.060 219043.060 0.006 0.004 0.004 1303.828 912.679 862.374 219043.060 219043.060 219043.060 1.000 1.000 1.000 1.000 1.000 219043.060 219043.060 219043.060 219043.060 219043.060 0.006 0.004 0.004 1303.828 912.679 862.374 219043.060 219043.060 219043.060 1.000 3.000 6.000 7.000 7.000 219043.060 564997.620 1007039.890 3057767.700 3057767.700 0.036 0.029 0.028 5994.285 12740.699 12038.456 305133.630 2050727.810 2050727.810 1.000 1.000 1.000 1.000 1.000 219043.060 219043.060 219043.060 219043.060 219043.060 0.006 0.004 0.004 1303.828 912.679 862.374 219043.060 219043.060 219043.060 NaN 26.000 NaN NaN 26.000 NaN
16 256 TRANSFER 4417.840 C1917019347 0.000 0.000 C104038589 2909698.670 2914116.510 0 0 C1917019347_C104038589 C1917019347_TRANSFER C104038589_TRANSFER C1917019347_C104038589_TRANSFER 10.000 1.000 1.000 1.000 1.000 1.000 4417.840 4417.840 4417.840 4417.840 4417.840 0.006 0.004 0.004 26.297 18.408 17.257 4417.840 4417.840 4417.840 2.000 4.000 14.000 17.000 17.000 223460.900 569415.460 3402190.150 5902084.970 5902084.970 0.083 0.071 0.066 20251.132 24592.021 23055.019 662038.200 2050727.810 2050727.810 1.000 1.000 1.000 1.000 1.000 4417.840 4417.840 4417.840 4417.840 4417.840 0.006 0.004 0.004 26.297 18.408 17.257 4417.840 4417.840 4417.840 1.000 1.000 1.000 1.000 1.000 4417.840 4417.840 4417.840 4417.840 4417.840 0.006 0.004 0.004 26.297 18.408 17.257 4417.840 4417.840 4417.840 1.000 1.000 3.000 4.000 4.000 4417.840 4417.840 1125749.540 1277791.700 1277791.700 0.018 0.017 0.016 6700.890 5324.132 4991.374 662038.200 662038.200 662038.200 1.000 1.000 1.000 1.000 1.000 4417.840 4417.840 4417.840 4417.840 4417.840 0.006 0.004 0.004 26.297 18.408 17.257 4417.840 4417.840 4417.840 NaN 2.000 NaN NaN 90.000 NaN
17 259 CASH_OUT 117729.860 C965354616 0.000 0.000 C104038589 2914116.510 3031846.370 0 0 C965354616_C104038589 C965354616_CASH_OUT C104038589_CASH_OUT C965354616_C104038589_CASH_OUT 10.000 1.000 1.000 1.000 1.000 1.000 117729.860 117729.860 117729.860 117729.860 117729.860 0.006 0.004 0.004 700.773 490.541 454.555 117729.860 117729.860 117729.860 3.000 5.000 15.000 18.000 18.000 341190.760 687145.320 3519920.010 6019814.830 6019814.830 0.089 0.075 0.069 20951.905 25082.562 23242.528 662038.200 2050727.810 2050727.810 1.000 1.000 1.000 1.000 1.000 117729.860 117729.860 117729.860 117729.860 117729.860 0.006 0.004 0.004 700.773 490.541 454.555 117729.860 117729.860 117729.860 1.000 1.000 1.000 1.000 1.000 117729.860 117729.860 117729.860 117729.860 117729.860 0.006 0.004 0.004 700.773 490.541 454.555 117729.860 117729.860 117729.860 2.000 4.000 7.000 8.000 8.000 336772.920 682727.480 1124769.750 3175497.560 3175497.560 0.042 0.033 0.031 6695.058 13231.240 12260.608 305133.630 2050727.810 2050727.810 1.000 1.000 1.000 1.000 1.000 117729.860 117729.860 117729.860 117729.860 117729.860 0.006 0.004 0.004 700.773 490.541 454.555 117729.860 117729.860 117729.860 NaN 3.000 NaN NaN 5.000 NaN
18 284 CASH_IN 118532.170 C872297469 3188564.020 3307096.190 C104038589 3031846.370 2913314.210 0 0 C872297469_C104038589 C872297469_CASH_IN C104038589_CASH_IN C872297469_C104038589_CASH_IN 11.000 1.000 1.000 1.000 1.000 1.000 118532.170 118532.170 118532.170 118532.170 118532.170 0.006 0.004 0.004 705.549 493.884 417.367 118532.170 118532.170 118532.170 1.000 5.000 16.000 17.000 19.000 118532.170 764856.560 3638452.180 5689179.990 6138347.000 0.095 0.071 0.067 21657.453 23704.917 21613.898 662038.200 2050727.810 2050727.810 1.000 1.000 1.000 1.000 1.000 118532.170 118532.170 118532.170 118532.170 118532.170 0.006 0.004 0.004 705.549 493.884 417.367 118532.170 118532.170 118532.170 1.000 1.000 1.000 1.000 1.000 118532.170 118532.170 118532.170 118532.170 118532.170 0.006 0.004 0.004 705.549 493.884 417.367 118532.170 118532.170 118532.170 1.000 1.000 6.000 6.000 7.000 118532.170 118532.170 1387932.890 1387932.890 1685057.740 0.036 0.025 0.025 8261.505 5783.054 5933.302 496826.440 496826.440 496826.440 1.000 1.000 1.000 1.000 1.000 118532.170 118532.170 118532.170 118532.170 118532.170 0.006 0.004 0.004 705.549 493.884 417.367 118532.170 118532.170 118532.170 NaN 25.000 NaN NaN 101.000 NaN
19 347 CASH_IN 465159.090 C527660802 132657.000 597816.090 C104038589 2913314.210 2448155.120 0 0 C527660802_C104038589 C527660802_CASH_IN C104038589_CASH_IN C527660802_C104038589_CASH_IN 14.000 1.000 1.000 1.000 1.000 1.000 465159.090 465159.090 465159.090 465159.090 465159.090 0.006 0.004 0.003 2768.804 1938.163 1384.402 465159.090 465159.090 465159.090 1.000 2.000 9.000 17.000 20.000 465159.090 583691.260 1725507.760 4103611.270 6603506.090 0.054 0.071 0.060 10270.880 17098.380 19653.292 465159.090 662038.200 2050727.810 1.000 1.000 1.000 1.000 1.000 465159.090 465159.090 465159.090 465159.090 465159.090 0.006 0.004 0.003 2768.804 1938.163 1384.402 465159.090 465159.090 465159.090 1.000 1.000 1.000 1.000 1.000 465159.090 465159.090 465159.090 465159.090 465159.090 0.006 0.004 0.003 2768.804 1938.163 1384.402 465159.090 465159.090 465159.090 1.000 2.000 4.000 7.000 8.000 465159.090 583691.260 1038362.440 1853091.980 2150216.830 0.024 0.029 0.024 6180.729 7721.217 6399.455 465159.090 496826.440 496826.440 1.000 1.000 1.000 1.000 1.000 465159.090 465159.090 465159.090 465159.090 465159.090 0.006 0.004 0.003 2768.804 1938.163 1384.402 465159.090 465159.090 465159.090 NaN 63.000 NaN NaN 63.000 NaN
20 348 CASH_OUT 36025.800 C999021425 256344.780 220318.970 C104038589 2448155.120 2484180.920 0 0 C999021425_C104038589 C999021425_CASH_OUT C104038589_CASH_OUT C999021425_C104038589_CASH_OUT 14.000 1.000 1.000 1.000 1.000 1.000 36025.800 36025.800 36025.800 36025.800 36025.800 0.006 0.004 0.003 214.439 150.108 107.220 36025.800 36025.800 36025.800 2.000 3.000 10.000 18.000 21.000 501184.890 619717.060 1761533.560 4139637.070 6639531.890 0.060 0.075 0.062 10485.319 17248.488 19760.512 465159.090 662038.200 2050727.810 1.000 1.000 1.000 1.000 1.000 36025.800 36025.800 36025.800 36025.800 36025.800 0.006 0.004 0.003 214.439 150.108 107.220 36025.800 36025.800 36025.800 1.000 1.000 1.000 1.000 1.000 36025.800 36025.800 36025.800 36025.800 36025.800 0.006 0.004 0.003 214.439 150.108 107.220 36025.800 36025.800 36025.800 1.000 1.000 5.000 8.000 9.000 36025.800 36025.800 718753.280 1160795.550 3211523.360 0.030 0.033 0.027 4278.293 4836.648 9558.105 305133.630 305133.630 2050727.810 1.000 1.000 1.000 1.000 1.000 36025.800 36025.800 36025.800 36025.800 36025.800 0.006 0.004 0.003 214.439 150.108 107.220 36025.800 36025.800 36025.800 NaN 1.000 NaN NaN 89.000 NaN
21 520 CASH_IN 34831.190 C181328714 4163684.040 4198515.230 C104038589 2484180.920 2449349.720 0 0 C181328714_C104038589 C181328714_CASH_IN C104038589_CASH_IN C181328714_C104038589_CASH_IN 21.000 1.000 1.000 1.000 1.000 1.000 34831.190 34831.190 34831.190 34831.190 34831.190 0.006 0.004 0.003 207.329 145.130 103.664 34831.190 34831.190 34831.190 1.000 1.000 1.000 4.000 9.000 34831.190 34831.190 34831.190 654548.250 1341693.570 0.006 0.017 0.027 207.329 2727.284 3993.136 34831.190 465159.090 465159.090 1.000 1.000 1.000 1.000 1.000 34831.190 34831.190 34831.190 34831.190 34831.190 0.006 0.004 0.003 207.329 145.130 103.664 34831.190 34831.190 34831.190 1.000 1.000 1.000 1.000 1.000 34831.190 34831.190 34831.190 34831.190 34831.190 0.006 0.004 0.003 207.329 145.130 103.664 34831.190 34831.190 34831.190 1.000 1.000 1.000 3.000 3.000 34831.190 34831.190 34831.190 618522.450 618522.450 0.006 0.013 0.009 207.329 2577.177 1840.841 34831.190 465159.090 465159.090 1.000 1.000 1.000 1.000 1.000 34831.190 34831.190 34831.190 34831.190 34831.190 0.006 0.004 0.003 207.329 145.130 103.664 34831.190 34831.190 34831.190 NaN 172.000 NaN NaN 173.000 NaN
22 587 CASH_OUT 168424.450 C1097481164 10002.000 0.000 C104038589 2449349.720 2617774.170 0 0 C1097481164_C104038589 C1097481164_CASH_OUT C104038589_CASH_OUT C1097481164_C104038589_CASH_OUT 24.000 1.000 1.000 1.000 1.000 1.000 168424.450 168424.450 168424.450 168424.450 168424.450 0.006 0.004 0.003 1002.526 701.769 501.263 168424.450 168424.450 168424.450 1.000 2.000 2.000 3.000 8.000 168424.450 203255.640 203255.640 239281.440 1164163.460 0.012 0.013 0.024 1209.855 997.006 3464.772 168424.450 168424.450 465159.090 1.000 1.000 1.000 1.000 1.000 168424.450 168424.450 168424.450 168424.450 168424.450 0.006 0.004 0.003 1002.526 701.769 501.263 168424.450 168424.450 168424.450 1.000 1.000 1.000 1.000 1.000 168424.450 168424.450 168424.450 168424.450 168424.450 0.006 0.004 0.003 1002.526 701.769 501.263 168424.450 168424.450 168424.450 1.000 1.000 1.000 2.000 4.000 168424.450 168424.450 168424.450 204450.250 541223.170 0.006 0.008 0.012 1002.526 851.876 1610.783 168424.450 168424.450 219043.060 1.000 1.000 1.000 1.000 1.000 168424.450 168424.450 168424.450 168424.450 168424.450 0.006 0.004 0.003 1002.526 701.769 501.263 168424.450 168424.450 168424.450 NaN 67.000 NaN NaN 239.000 NaN

4.4 Velocity features¶

In [36]:
#aml_data = aml_data.sort_values(by = ['nameDest','step']).reset_index(drop=True)
In [37]:
for i in ['nameOrig','nameDest','nameOrig_nameDest','nameOrig_type','nameDest_type','nameOrig_nameDest_type']:
    aml_data[i + '_' + 'txnCount_velocity_ratio_over_7day'] = aml_data[i + '_' + 'rolling_txn_count_1day'] / aml_data[i + '_' + 'rolling_txn_count_mean_7day'] 
    aml_data[i + '_' + 'txnCount_velocity_ratio_over_10day'] = aml_data[i + '_' + 'rolling_txn_count_1day'] / aml_data[i + '_' + 'rolling_txn_count_mean_10day'] 
    aml_data[i + '_' + 'txnCount_velocity_ratio_over_14day'] = aml_data[i + '_' + 'rolling_txn_count_1day'] / aml_data[i + '_' + 'rolling_txn_count_mean_14day']
    
    aml_data[i + '_' + 'amount_velocity_ratio_over_7day'] = aml_data[i + '_' + 'rolling_txn_sum_1day'] / aml_data[i + '_' + 'rolling_txn_amount_mean_7day'] 
    aml_data[i + '_' + 'amount_velocity_ratio_over_10day'] = aml_data[i + '_' + 'rolling_txn_sum_1day'] / aml_data[i + '_' + 'rolling_txn_amount_mean_10day'] 
    aml_data[i + '_' + 'amount_velocity_ratio_over_14day'] = aml_data[i + '_' + 'rolling_txn_sum_1day'] / aml_data[i + '_' + 'rolling_txn_amount_mean_14day'] 
    
    #aml_data[i + '_' + 'amount_median_velocity_ratio_over_7day'] = aml_data[i + '_' + 'rolling_txn_sum_1day'] / aml_data[i + '_' + 'rolling_txn_amount_median_7day'] 
    #aml_data[i + '_' + 'amount_median_velocity_ratio_over_10day'] = aml_data[i + '_' + 'rolling_txn_sum_1day'] / aml_data[i + '_' + 'rolling_txn_amount_median_10day'] 
    #aml_data[i + '_' + 'amount_median_velocity_ratio_over_14day'] = aml_data[i + '_' + 'rolling_txn_sum_1day'] / aml_data[i + '_' + 'rolling_txn_amount_median_14day'] 

    aml_data[i + '_' + 'amount_max_velocity_ratio_over_7day'] = aml_data[i + '_' + 'rolling_txn_sum_1day'] / aml_data[i + '_' + 'rolling_txn_amount_max_7day'] 
    aml_data[i + '_' + 'amount_max_velocity_ratio_over_10day'] = aml_data[i + '_' + 'rolling_txn_sum_1day'] / aml_data[i + '_' + 'rolling_txn_amount_max_10day'] 
    aml_data[i + '_' + 'amount_max_velocity_ratio_over_14day'] = aml_data[i + '_' + 'rolling_txn_sum_1day'] / aml_data[i + '_' + 'rolling_txn_amount_max_14day']

4.5 Had previous fraud¶

Extremely important to exclude current row while calculating cumulative sum for these candidate variables (else you will include information on target)¶

In [38]:
for i in ['nameOrig','nameDest','nameOrig_nameDest','nameOrig_type','nameDest_type','nameOrig_nameDest_type']:
    #print(i)
    #print(i + '_' + 'time_since_last_txn')
    aml_data = aml_data.sort_values(by = [i,'step']).reset_index(drop=True)
    aml_data[i + '_' + 'had_prev_fraud'] = aml_data.groupby([i])['isFraud'].apply(lambda x: x.cumsum().shift().bfill())
In [39]:
aml_data[aml_data.nameDest == 'C1013511446'].sort_values(by = ['step'])
Out[39]:
step type amount nameOrig oldbalanceOrg newbalanceOrig nameDest oldbalanceDest newbalanceDest isFraud isFlaggedFraud nameOrig_nameDest nameOrig_type nameDest_type nameOrig_nameDest_type day nameOrig_rolling_txn_count_1day nameOrig_rolling_txn_count_3day nameOrig_rolling_txn_count_7day nameOrig_rolling_txn_count_10day nameOrig_rolling_txn_count_14day nameOrig_rolling_txn_sum_1day nameOrig_rolling_txn_sum_3day nameOrig_rolling_txn_sum_7day nameOrig_rolling_txn_sum_10day nameOrig_rolling_txn_sum_14day nameOrig_rolling_txn_count_mean_7day nameOrig_rolling_txn_count_mean_10day nameOrig_rolling_txn_count_mean_14day nameOrig_rolling_txn_amount_mean_7day nameOrig_rolling_txn_amount_mean_10day nameOrig_rolling_txn_amount_mean_14day nameOrig_rolling_txn_amount_max_7day nameOrig_rolling_txn_amount_max_10day nameOrig_rolling_txn_amount_max_14day nameDest_rolling_txn_count_1day nameDest_rolling_txn_count_3day nameDest_rolling_txn_count_7day nameDest_rolling_txn_count_10day nameDest_rolling_txn_count_14day nameDest_rolling_txn_sum_1day nameDest_rolling_txn_sum_3day nameDest_rolling_txn_sum_7day nameDest_rolling_txn_sum_10day nameDest_rolling_txn_sum_14day nameDest_rolling_txn_count_mean_7day nameDest_rolling_txn_count_mean_10day nameDest_rolling_txn_count_mean_14day nameDest_rolling_txn_amount_mean_7day nameDest_rolling_txn_amount_mean_10day nameDest_rolling_txn_amount_mean_14day nameDest_rolling_txn_amount_max_7day nameDest_rolling_txn_amount_max_10day nameDest_rolling_txn_amount_max_14day nameOrig_nameDest_rolling_txn_count_1day nameOrig_nameDest_rolling_txn_count_3day nameOrig_nameDest_rolling_txn_count_7day nameOrig_nameDest_rolling_txn_count_10day nameOrig_nameDest_rolling_txn_count_14day nameOrig_nameDest_rolling_txn_sum_1day nameOrig_nameDest_rolling_txn_sum_3day nameOrig_nameDest_rolling_txn_sum_7day nameOrig_nameDest_rolling_txn_sum_10day nameOrig_nameDest_rolling_txn_sum_14day nameOrig_nameDest_rolling_txn_count_mean_7day nameOrig_nameDest_rolling_txn_count_mean_10day nameOrig_nameDest_rolling_txn_count_mean_14day nameOrig_nameDest_rolling_txn_amount_mean_7day nameOrig_nameDest_rolling_txn_amount_mean_10day nameOrig_nameDest_rolling_txn_amount_mean_14day nameOrig_nameDest_rolling_txn_amount_max_7day nameOrig_nameDest_rolling_txn_amount_max_10day nameOrig_nameDest_rolling_txn_amount_max_14day nameOrig_type_rolling_txn_count_1day nameOrig_type_rolling_txn_count_3day nameOrig_type_rolling_txn_count_7day nameOrig_type_rolling_txn_count_10day nameOrig_type_rolling_txn_count_14day nameOrig_type_rolling_txn_sum_1day nameOrig_type_rolling_txn_sum_3day nameOrig_type_rolling_txn_sum_7day nameOrig_type_rolling_txn_sum_10day nameOrig_type_rolling_txn_sum_14day nameOrig_type_rolling_txn_count_mean_7day nameOrig_type_rolling_txn_count_mean_10day nameOrig_type_rolling_txn_count_mean_14day nameOrig_type_rolling_txn_amount_mean_7day nameOrig_type_rolling_txn_amount_mean_10day nameOrig_type_rolling_txn_amount_mean_14day nameOrig_type_rolling_txn_amount_max_7day nameOrig_type_rolling_txn_amount_max_10day nameOrig_type_rolling_txn_amount_max_14day nameDest_type_rolling_txn_count_1day nameDest_type_rolling_txn_count_3day nameDest_type_rolling_txn_count_7day nameDest_type_rolling_txn_count_10day nameDest_type_rolling_txn_count_14day nameDest_type_rolling_txn_sum_1day nameDest_type_rolling_txn_sum_3day nameDest_type_rolling_txn_sum_7day nameDest_type_rolling_txn_sum_10day nameDest_type_rolling_txn_sum_14day nameDest_type_rolling_txn_count_mean_7day nameDest_type_rolling_txn_count_mean_10day nameDest_type_rolling_txn_count_mean_14day nameDest_type_rolling_txn_amount_mean_7day nameDest_type_rolling_txn_amount_mean_10day nameDest_type_rolling_txn_amount_mean_14day nameDest_type_rolling_txn_amount_max_7day nameDest_type_rolling_txn_amount_max_10day nameDest_type_rolling_txn_amount_max_14day nameOrig_nameDest_type_rolling_txn_count_1day nameOrig_nameDest_type_rolling_txn_count_3day 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458 227 TRANSFER 2531127.630 C1008129833 0.000 0.000 C1013511446 10619072.490 13150200.120 0 0 C1008129833_C1013511446 C1008129833_TRANSFER C1013511446_TRANSFER C1008129833_C1013511446_TRANSFER 9.000 1.000 1.000 1.000 1.000 1.000 2531127.630 2531127.630 2531127.630 2531127.630 2531127.630 0.006 0.004 0.004 15066.236 11150.342 11150.342 2531127.630 2531127.630 2531127.630 2.000 3.000 8.000 28.000 28.000 2897051.100 3205840.680 4866337.930 19521322.570 19521322.570 0.048 0.123 0.123 28966.297 85997.016 85997.016 2531127.630 3134107.800 3134107.800 1.000 1.000 1.000 1.000 1.000 2531127.630 2531127.630 2531127.630 2531127.630 2531127.630 0.006 0.004 0.004 15066.236 11150.342 11150.342 2531127.630 2531127.630 2531127.630 1.000 1.000 1.000 1.000 1.000 2531127.630 2531127.630 2531127.630 2531127.630 2531127.630 0.006 0.004 0.004 15066.236 11150.342 11150.342 2531127.630 2531127.630 2531127.630 2.000 2.000 2.000 7.000 7.000 2897051.100 2897051.100 2897051.100 11523122.150 11523122.150 0.012 0.031 0.031 17244.352 50762.653 50762.653 2531127.630 2877376.240 2877376.240 1.000 1.000 1.000 1.000 1.000 2531127.630 2531127.630 2531127.630 2531127.630 2531127.630 0.006 0.004 0.004 15066.236 11150.342 11150.342 2531127.630 2531127.630 2531127.630 NaN 13.000 NaN NaN 13.000 NaN 168.000 227.000 227.000 168.000 227.000 227.000 1.000 1.000 1.000 42.000 16.214 16.214 100.015 33.688 33.688 1.145 0.924 0.924 168.000 227.000 227.000 168.000 227.000 227.000 1.000 1.000 1.000 168.000 227.000 227.000 168.000 227.000 227.000 1.000 1.000 1.000 168.000 64.857 64.857 168.000 57.071 57.071 1.145 1.007 1.007 168.000 227.000 227.000 168.000 227.000 227.000 1.000 1.000 1.000 NaN 2.000 NaN NaN 0.000 NaN
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51362 249 TRANSFER 693889.520 C1993947775 0.000 0.000 C1013511446 13108249.510 13802139.040 0 0 C1993947775_C1013511446 C1993947775_TRANSFER C1013511446_TRANSFER C1993947775_C1013511446_TRANSFER 10.000 1.000 1.000 1.000 1.000 1.000 693889.520 693889.520 693889.520 693889.520 693889.520 0.006 0.004 0.004 4130.295 2891.206 2786.705 693889.520 693889.520 693889.520 3.000 4.000 9.000 28.000 30.000 3266967.750 3632891.220 5147103.920 17123054.890 20257162.690 0.054 0.117 0.120 30637.523 71346.062 81354.067 2531127.630 2986135.550 3134107.800 1.000 1.000 1.000 1.000 1.000 693889.520 693889.520 693889.520 693889.520 693889.520 0.006 0.004 0.004 4130.295 2891.206 2786.705 693889.520 693889.520 693889.520 1.000 1.000 1.000 1.000 1.000 693889.520 693889.520 693889.520 693889.520 693889.520 0.006 0.004 0.004 4130.295 2891.206 2786.705 693889.520 693889.520 693889.520 2.000 3.000 3.000 8.000 8.000 3225017.150 3590940.620 3590940.620 12217011.670 12217011.670 0.018 0.033 0.032 21374.647 50904.215 49064.304 2531127.630 2877376.240 2877376.240 1.000 1.000 1.000 1.000 1.000 693889.520 693889.520 693889.520 693889.520 693889.520 0.006 0.004 0.004 4130.295 2891.206 2786.705 693889.520 693889.520 693889.520 NaN 14.000 NaN NaN 22.000 NaN 168.000 240.000 249.000 168.000 240.000 249.000 1.000 1.000 1.000 56.000 25.714 24.900 106.633 45.790 40.157 1.291 1.094 1.042 168.000 240.000 249.000 168.000 240.000 249.000 1.000 1.000 1.000 168.000 240.000 249.000 168.000 240.000 249.000 1.000 1.000 1.000 112.000 60.000 62.250 150.880 63.355 65.730 1.274 1.121 1.121 168.000 240.000 249.000 168.000 240.000 249.000 1.000 1.000 1.000 NaN 2.000 NaN NaN 0.000 NaN
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66880 302 CASH_OUT 374092.820 C361292479 0.000 0.000 C1013511446 13903086.330 14277179.160 0 0 C361292479_C1013511446 C361292479_CASH_OUT C1013511446_CASH_OUT C361292479_C1013511446_CASH_OUT 12.000 1.000 1.000 1.000 1.000 1.000 374092.820 374092.820 374092.820 374092.820 374092.820 0.006 0.004 0.003 2226.743 1558.720 1238.718 374092.820 374092.820 374092.820 1.000 4.000 10.000 12.000 32.000 374092.820 1210880.240 5092002.480 6077218.170 20732202.810 0.060 0.050 0.106 30309.539 25321.742 68649.678 2531127.630 2531127.630 3134107.800 1.000 1.000 1.000 1.000 1.000 374092.820 374092.820 374092.820 374092.820 374092.820 0.006 0.004 0.003 2226.743 1558.720 1238.718 374092.820 374092.820 374092.820 1.000 1.000 1.000 1.000 1.000 374092.820 374092.820 374092.820 374092.820 374092.820 0.006 0.004 0.003 2226.743 1558.720 1238.718 374092.820 374092.820 374092.820 1.000 2.000 4.000 6.000 14.000 374092.820 475040.120 982456.990 1967672.680 6208627.440 0.024 0.025 0.046 5847.958 8198.636 20558.369 374092.820 530141.560 2539898.070 1.000 1.000 1.000 1.000 1.000 374092.820 374092.820 374092.820 374092.820 374092.820 0.006 0.004 0.003 2226.743 1558.720 1238.718 374092.820 374092.820 374092.820 NaN 51.000 NaN NaN 51.000 NaN 168.000 240.000 302.000 168.000 240.000 302.000 1.000 1.000 1.000 16.800 20.000 9.438 12.342 14.774 5.449 0.148 0.148 0.119 168.000 240.000 302.000 168.000 240.000 302.000 1.000 1.000 1.000 168.000 240.000 302.000 168.000 240.000 302.000 1.000 1.000 1.000 42.000 40.000 21.571 63.970 45.629 18.197 1.000 0.706 0.147 168.000 240.000 302.000 168.000 240.000 302.000 1.000 1.000 1.000 NaN 2.000 NaN NaN 2.000 NaN
54632 379 CASH_OUT 24859.810 C2057847261 48951.000 24091.190 C1013511446 14342024.600 14366884.410 0 0 C2057847261_C1013511446 C2057847261_CASH_OUT C1013511446_CASH_OUT C2057847261_C1013511446_CASH_OUT 15.000 1.000 1.000 1.000 1.000 1.000 24859.810 24859.810 24859.810 24859.810 24859.810 0.006 0.004 0.003 147.975 103.583 73.988 24859.810 24859.810 24859.810 2.000 2.000 8.000 11.000 14.000 89705.260 89705.260 4197636.600 5013843.050 6166923.430 0.048 0.046 0.042 24985.932 20891.013 18353.939 2531127.630 2531127.630 2531127.630 1.000 1.000 1.000 1.000 1.000 24859.810 24859.810 24859.810 24859.810 24859.810 0.006 0.004 0.003 147.975 103.583 73.988 24859.810 24859.810 24859.810 1.000 1.000 1.000 1.000 1.000 24859.810 24859.810 24859.810 24859.810 24859.810 0.006 0.004 0.003 147.975 103.583 73.988 24859.810 24859.810 24859.810 2.000 2.000 4.000 6.000 8.000 89705.260 89705.260 564745.380 1072162.250 2057377.940 0.024 0.025 0.024 3361.580 4467.343 6123.149 374092.820 374092.820 530141.560 1.000 1.000 1.000 1.000 1.000 24859.810 24859.810 24859.810 24859.810 24859.810 0.006 0.004 0.003 147.975 103.583 73.988 24859.810 24859.810 24859.810 NaN 77.000 NaN NaN 77.000 NaN 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 42.000 43.636 48.000 3.590 4.294 4.888 0.035 0.035 0.035 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 84.000 80.000 84.000 26.685 20.080 14.650 0.240 0.240 0.169 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 NaN 2.000 NaN NaN 2.000 NaN
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79462 402 TRANSFER 1404263.060 C605208523 3080.000 0.000 C1013511446 14366884.410 15771147.470 0 0 C605208523_C1013511446 C605208523_TRANSFER C1013511446_TRANSFER C605208523_C1013511446_TRANSFER 16.000 1.000 1.000 1.000 1.000 1.000 1404263.060 1404263.060 1404263.060 1404263.060 1404263.060 0.006 0.004 0.003 8358.709 5851.096 4179.354 1404263.060 1404263.060 1404263.060 3.000 3.000 7.000 10.000 15.000 1493968.320 1493968.320 2704848.560 5910689.240 7571186.490 0.042 0.042 0.045 16100.289 24627.872 22533.293 1404263.060 2531127.630 2531127.630 1.000 1.000 1.000 1.000 1.000 1404263.060 1404263.060 1404263.060 1404263.060 1404263.060 0.006 0.004 0.003 8358.709 5851.096 4179.354 1404263.060 1404263.060 1404263.060 1.000 1.000 1.000 1.000 1.000 1404263.060 1404263.060 1404263.060 1404263.060 1404263.060 0.006 0.004 0.003 8358.709 5851.096 4179.354 1404263.060 1404263.060 1404263.060 1.000 1.000 2.000 4.000 4.000 1404263.060 1404263.060 2098152.580 4995203.680 4995203.680 0.012 0.017 0.012 12489.003 20813.349 14866.678 1404263.060 2531127.630 2531127.630 1.000 1.000 1.000 1.000 1.000 1404263.060 1404263.060 1404263.060 1404263.060 1404263.060 0.006 0.004 0.003 8358.709 5851.096 4179.354 1404263.060 1404263.060 1404263.060 NaN 23.000 NaN NaN 153.000 NaN 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 72.000 72.000 67.200 92.791 60.662 66.300 1.064 0.590 0.590 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 84.000 60.000 84.000 112.440 67.469 94.457 1.000 0.555 0.555 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 NaN 2.000 NaN NaN 0.000 NaN

4.6 Change in balance¶

In [40]:
aml_data['changeBalanceOrg_prcnt'] = ((aml_data['newbalanceOrig'] - aml_data['oldbalanceOrg'])*100) / (aml_data['oldbalanceOrg']+1)
aml_data['changeBalanceDest_prcnt'] = ((aml_data['newbalanceDest'] - aml_data['oldbalanceDest'])*100) / (aml_data['oldbalanceDest']+1)
In [41]:
np.max(aml_data['changeBalanceOrg_prcnt'])
Out[41]:
72505871.0

5. Train Test Split¶

In [42]:
# drop identifiers
model_data = aml_data.drop(columns = ['nameOrig','nameDest','nameOrig_nameDest','nameOrig_type','nameDest_type','nameOrig_nameDest_type','isFlaggedFraud'])
model_data.head()
Out[42]:
step type amount oldbalanceOrg newbalanceOrig oldbalanceDest newbalanceDest isFraud day nameOrig_rolling_txn_count_1day nameOrig_rolling_txn_count_3day nameOrig_rolling_txn_count_7day nameOrig_rolling_txn_count_10day nameOrig_rolling_txn_count_14day nameOrig_rolling_txn_sum_1day nameOrig_rolling_txn_sum_3day nameOrig_rolling_txn_sum_7day nameOrig_rolling_txn_sum_10day nameOrig_rolling_txn_sum_14day nameOrig_rolling_txn_count_mean_7day nameOrig_rolling_txn_count_mean_10day nameOrig_rolling_txn_count_mean_14day nameOrig_rolling_txn_amount_mean_7day nameOrig_rolling_txn_amount_mean_10day nameOrig_rolling_txn_amount_mean_14day nameOrig_rolling_txn_amount_max_7day nameOrig_rolling_txn_amount_max_10day nameOrig_rolling_txn_amount_max_14day nameDest_rolling_txn_count_1day nameDest_rolling_txn_count_3day nameDest_rolling_txn_count_7day nameDest_rolling_txn_count_10day nameDest_rolling_txn_count_14day nameDest_rolling_txn_sum_1day nameDest_rolling_txn_sum_3day nameDest_rolling_txn_sum_7day nameDest_rolling_txn_sum_10day nameDest_rolling_txn_sum_14day nameDest_rolling_txn_count_mean_7day nameDest_rolling_txn_count_mean_10day nameDest_rolling_txn_count_mean_14day nameDest_rolling_txn_amount_mean_7day nameDest_rolling_txn_amount_mean_10day nameDest_rolling_txn_amount_mean_14day nameDest_rolling_txn_amount_max_7day nameDest_rolling_txn_amount_max_10day nameDest_rolling_txn_amount_max_14day nameOrig_nameDest_rolling_txn_count_1day nameOrig_nameDest_rolling_txn_count_3day nameOrig_nameDest_rolling_txn_count_7day nameOrig_nameDest_rolling_txn_count_10day nameOrig_nameDest_rolling_txn_count_14day nameOrig_nameDest_rolling_txn_sum_1day nameOrig_nameDest_rolling_txn_sum_3day nameOrig_nameDest_rolling_txn_sum_7day nameOrig_nameDest_rolling_txn_sum_10day nameOrig_nameDest_rolling_txn_sum_14day nameOrig_nameDest_rolling_txn_count_mean_7day nameOrig_nameDest_rolling_txn_count_mean_10day nameOrig_nameDest_rolling_txn_count_mean_14day nameOrig_nameDest_rolling_txn_amount_mean_7day nameOrig_nameDest_rolling_txn_amount_mean_10day nameOrig_nameDest_rolling_txn_amount_mean_14day nameOrig_nameDest_rolling_txn_amount_max_7day nameOrig_nameDest_rolling_txn_amount_max_10day nameOrig_nameDest_rolling_txn_amount_max_14day nameOrig_type_rolling_txn_count_1day nameOrig_type_rolling_txn_count_3day nameOrig_type_rolling_txn_count_7day nameOrig_type_rolling_txn_count_10day nameOrig_type_rolling_txn_count_14day nameOrig_type_rolling_txn_sum_1day nameOrig_type_rolling_txn_sum_3day nameOrig_type_rolling_txn_sum_7day nameOrig_type_rolling_txn_sum_10day nameOrig_type_rolling_txn_sum_14day nameOrig_type_rolling_txn_count_mean_7day nameOrig_type_rolling_txn_count_mean_10day nameOrig_type_rolling_txn_count_mean_14day nameOrig_type_rolling_txn_amount_mean_7day nameOrig_type_rolling_txn_amount_mean_10day nameOrig_type_rolling_txn_amount_mean_14day nameOrig_type_rolling_txn_amount_max_7day nameOrig_type_rolling_txn_amount_max_10day nameOrig_type_rolling_txn_amount_max_14day nameDest_type_rolling_txn_count_1day nameDest_type_rolling_txn_count_3day nameDest_type_rolling_txn_count_7day nameDest_type_rolling_txn_count_10day nameDest_type_rolling_txn_count_14day nameDest_type_rolling_txn_sum_1day nameDest_type_rolling_txn_sum_3day nameDest_type_rolling_txn_sum_7day nameDest_type_rolling_txn_sum_10day nameDest_type_rolling_txn_sum_14day nameDest_type_rolling_txn_count_mean_7day nameDest_type_rolling_txn_count_mean_10day nameDest_type_rolling_txn_count_mean_14day nameDest_type_rolling_txn_amount_mean_7day nameDest_type_rolling_txn_amount_mean_10day nameDest_type_rolling_txn_amount_mean_14day nameDest_type_rolling_txn_amount_max_7day nameDest_type_rolling_txn_amount_max_10day nameDest_type_rolling_txn_amount_max_14day nameOrig_nameDest_type_rolling_txn_count_1day nameOrig_nameDest_type_rolling_txn_count_3day nameOrig_nameDest_type_rolling_txn_count_7day nameOrig_nameDest_type_rolling_txn_count_10day nameOrig_nameDest_type_rolling_txn_count_14day nameOrig_nameDest_type_rolling_txn_sum_1day nameOrig_nameDest_type_rolling_txn_sum_3day nameOrig_nameDest_type_rolling_txn_sum_7day nameOrig_nameDest_type_rolling_txn_sum_10day nameOrig_nameDest_type_rolling_txn_sum_14day nameOrig_nameDest_type_rolling_txn_count_mean_7day nameOrig_nameDest_type_rolling_txn_count_mean_10day nameOrig_nameDest_type_rolling_txn_count_mean_14day nameOrig_nameDest_type_rolling_txn_amount_mean_7day nameOrig_nameDest_type_rolling_txn_amount_mean_10day nameOrig_nameDest_type_rolling_txn_amount_mean_14day nameOrig_nameDest_type_rolling_txn_amount_max_7day nameOrig_nameDest_type_rolling_txn_amount_max_10day nameOrig_nameDest_type_rolling_txn_amount_max_14day nameOrig_time_since_last_txn nameDest_time_since_last_txn nameOrig_nameDest_time_since_last_txn nameOrig_type_time_since_last_txn nameDest_type_time_since_last_txn nameOrig_nameDest_type_time_since_last_txn nameOrig_txnCount_velocity_ratio_over_7day nameOrig_txnCount_velocity_ratio_over_10day nameOrig_txnCount_velocity_ratio_over_14day nameOrig_amount_velocity_ratio_over_7day nameOrig_amount_velocity_ratio_over_10day nameOrig_amount_velocity_ratio_over_14day nameOrig_amount_max_velocity_ratio_over_7day nameOrig_amount_max_velocity_ratio_over_10day nameOrig_amount_max_velocity_ratio_over_14day nameDest_txnCount_velocity_ratio_over_7day nameDest_txnCount_velocity_ratio_over_10day nameDest_txnCount_velocity_ratio_over_14day nameDest_amount_velocity_ratio_over_7day nameDest_amount_velocity_ratio_over_10day nameDest_amount_velocity_ratio_over_14day nameDest_amount_max_velocity_ratio_over_7day nameDest_amount_max_velocity_ratio_over_10day nameDest_amount_max_velocity_ratio_over_14day nameOrig_nameDest_txnCount_velocity_ratio_over_7day nameOrig_nameDest_txnCount_velocity_ratio_over_10day nameOrig_nameDest_txnCount_velocity_ratio_over_14day nameOrig_nameDest_amount_velocity_ratio_over_7day nameOrig_nameDest_amount_velocity_ratio_over_10day nameOrig_nameDest_amount_velocity_ratio_over_14day nameOrig_nameDest_amount_max_velocity_ratio_over_7day nameOrig_nameDest_amount_max_velocity_ratio_over_10day nameOrig_nameDest_amount_max_velocity_ratio_over_14day nameOrig_type_txnCount_velocity_ratio_over_7day nameOrig_type_txnCount_velocity_ratio_over_10day nameOrig_type_txnCount_velocity_ratio_over_14day nameOrig_type_amount_velocity_ratio_over_7day nameOrig_type_amount_velocity_ratio_over_10day nameOrig_type_amount_velocity_ratio_over_14day nameOrig_type_amount_max_velocity_ratio_over_7day nameOrig_type_amount_max_velocity_ratio_over_10day nameOrig_type_amount_max_velocity_ratio_over_14day nameDest_type_txnCount_velocity_ratio_over_7day nameDest_type_txnCount_velocity_ratio_over_10day nameDest_type_txnCount_velocity_ratio_over_14day nameDest_type_amount_velocity_ratio_over_7day nameDest_type_amount_velocity_ratio_over_10day nameDest_type_amount_velocity_ratio_over_14day nameDest_type_amount_max_velocity_ratio_over_7day nameDest_type_amount_max_velocity_ratio_over_10day nameDest_type_amount_max_velocity_ratio_over_14day nameOrig_nameDest_type_txnCount_velocity_ratio_over_7day nameOrig_nameDest_type_txnCount_velocity_ratio_over_10day nameOrig_nameDest_type_txnCount_velocity_ratio_over_14day nameOrig_nameDest_type_amount_velocity_ratio_over_7day nameOrig_nameDest_type_amount_velocity_ratio_over_10day nameOrig_nameDest_type_amount_velocity_ratio_over_14day nameOrig_nameDest_type_amount_max_velocity_ratio_over_7day nameOrig_nameDest_type_amount_max_velocity_ratio_over_10day nameOrig_nameDest_type_amount_max_velocity_ratio_over_14day nameOrig_had_prev_fraud nameDest_had_prev_fraud nameOrig_nameDest_had_prev_fraud nameOrig_type_had_prev_fraud nameDest_type_had_prev_fraud nameOrig_nameDest_type_had_prev_fraud changeBalanceOrg_prcnt changeBalanceDest_prcnt
0 289 CASH_IN 223513.230 2911285.730 3134798.970 482434.060 258920.820 0 12.000 1.000 1.000 1.000 1.000 1.000 223513.230 223513.230 223513.230 223513.230 223513.230 0.006 0.004 0.003 1330.436 931.305 773.402 223513.230 223513.230 223513.230 3.000 3.000 5.000 5.000 5.000 321996.020 321996.020 1240916.250 1240916.250 1240916.250 0.030 0.021 0.017 7386.406 5170.484 4293.828 743924.160 743924.160 743924.160 1.000 1.000 1.000 1.000 1.000 223513.230 223513.230 223513.230 223513.230 223513.230 0.006 0.004 0.003 1330.436 931.305 773.402 223513.230 223513.230 223513.230 1.000 1.000 1.000 1.000 1.000 223513.230 223513.230 223513.230 223513.230 223513.230 0.006 0.004 0.003 1330.436 931.305 773.402 223513.230 223513.230 223513.230 2.000 2.000 3.000 3.000 3.000 316001.640 316001.640 490997.710 490997.710 490997.710 0.018 0.013 0.010 2922.605 2045.824 1698.954 223513.230 223513.230 223513.230 1.000 1.000 1.000 1.000 1.000 223513.230 223513.230 223513.230 223513.230 223513.230 0.006 0.004 0.003 1330.436 931.305 773.402 223513.230 223513.230 223513.230 NaN 5.000 NaN NaN 5.000 NaN 168.000 240.000 289.000 168.000 240.000 289.000 1.000 1.000 1.000 100.800 144.000 173.400 43.593 62.276 74.990 0.433 0.433 0.433 168.000 240.000 289.000 168.000 240.000 289.000 1.000 1.000 1.000 168.000 240.000 289.000 168.000 240.000 289.000 1.000 1.000 1.000 112.000 160.000 192.667 108.123 154.462 185.998 1.414 1.414 1.414 168.000 240.000 289.000 168.000 240.000 289.000 1.000 1.000 1.000 NaN 0.000 NaN NaN 0.000 NaN 7.677 -46.330
1 259 CASH_OUT 163976.410 0.000 0.000 2281442.130 2445418.540 0 10.000 1.000 1.000 1.000 1.000 1.000 163976.410 163976.410 163976.410 163976.410 163976.410 0.006 0.004 0.004 976.050 683.235 633.114 163976.410 163976.410 163976.410 1.000 4.000 8.000 12.000 12.000 163976.410 1101733.320 2208005.030 3036206.260 3036206.260 0.048 0.050 0.046 13142.887 12650.859 11722.804 787971.490 787971.490 787971.490 1.000 1.000 1.000 1.000 1.000 163976.410 163976.410 163976.410 163976.410 163976.410 0.006 0.004 0.004 976.050 683.235 633.114 163976.410 163976.410 163976.410 1.000 1.000 1.000 1.000 1.000 163976.410 163976.410 163976.410 163976.410 163976.410 0.006 0.004 0.004 976.050 683.235 633.114 163976.410 163976.410 163976.410 1.000 3.000 3.000 5.000 5.000 163976.410 810348.570 810348.570 1209945.550 1209945.550 0.018 0.021 0.019 4823.503 5041.440 4671.604 411102.030 411102.030 411102.030 1.000 1.000 1.000 1.000 1.000 163976.410 163976.410 163976.410 163976.410 163976.410 0.006 0.004 0.004 976.050 683.235 633.114 163976.410 163976.410 163976.410 NaN 24.000 NaN NaN 24.000 NaN 168.000 240.000 259.000 168.000 240.000 259.000 1.000 1.000 1.000 21.000 20.000 21.583 12.476 12.962 13.988 0.208 0.208 0.208 168.000 240.000 259.000 168.000 240.000 259.000 1.000 1.000 1.000 168.000 240.000 259.000 168.000 240.000 259.000 1.000 1.000 1.000 56.000 48.000 51.800 33.995 32.526 35.101 0.399 0.399 0.399 168.000 240.000 259.000 168.000 240.000 259.000 1.000 1.000 1.000 NaN 0.000 NaN NaN 0.000 NaN 0.000 7.187
2 353 CASH_IN 71801.780 327251.000 399052.780 321931.140 250129.350 0 14.000 1.000 1.000 1.000 1.000 1.000 71801.780 71801.780 71801.780 71801.780 71801.780 0.006 0.004 0.003 427.392 299.174 213.696 71801.780 71801.780 71801.780 1.000 2.000 3.000 3.000 3.000 71801.780 154655.900 393732.920 393732.920 393732.920 0.018 0.013 0.009 2343.648 1640.554 1171.824 239077.020 239077.020 239077.020 1.000 1.000 1.000 1.000 1.000 71801.780 71801.780 71801.780 71801.780 71801.780 0.006 0.004 0.003 427.392 299.174 213.696 71801.780 71801.780 71801.780 1.000 1.000 1.000 1.000 1.000 71801.780 71801.780 71801.780 71801.780 71801.780 0.006 0.004 0.003 427.392 299.174 213.696 71801.780 71801.780 71801.780 1.000 1.000 1.000 1.000 1.000 71801.780 71801.780 71801.780 71801.780 71801.780 0.006 0.004 0.003 427.392 299.174 213.696 71801.780 71801.780 71801.780 1.000 1.000 1.000 1.000 1.000 71801.780 71801.780 71801.780 71801.780 71801.780 0.006 0.004 0.003 427.392 299.174 213.696 71801.780 71801.780 71801.780 NaN 24.000 NaN NaN NaN NaN 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 56.000 80.000 112.000 30.637 43.767 61.274 0.300 0.300 0.300 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 NaN 0.000 NaN NaN 0.000 NaN 21.941 -22.303
3 159 CASH_OUT 377853.580 20791.000 0.000 1846032.140 2596929.660 0 6.000 1.000 1.000 1.000 1.000 1.000 377853.580 377853.580 377853.580 377853.580 377853.580 0.006 0.006 0.006 2376.438 2376.438 2376.438 377853.580 377853.580 377853.580 2.000 4.000 6.000 6.000 6.000 456275.200 2223885.720 2669216.740 2669216.740 2669216.740 0.038 0.038 0.038 16787.527 16787.527 16787.527 1358478.670 1358478.670 1358478.670 1.000 1.000 1.000 1.000 1.000 377853.580 377853.580 377853.580 377853.580 377853.580 0.006 0.006 0.006 2376.438 2376.438 2376.438 377853.580 377853.580 377853.580 1.000 1.000 1.000 1.000 1.000 377853.580 377853.580 377853.580 377853.580 377853.580 0.006 0.006 0.006 2376.438 2376.438 2376.438 377853.580 377853.580 377853.580 2.000 3.000 3.000 3.000 3.000 456275.200 865407.050 865407.050 865407.050 865407.050 0.019 0.019 0.019 5442.812 5442.812 5442.812 409131.850 409131.850 409131.850 1.000 1.000 1.000 1.000 1.000 377853.580 377853.580 377853.580 377853.580 377853.580 0.006 0.006 0.006 2376.438 2376.438 2376.438 377853.580 377853.580 377853.580 NaN 19.000 NaN NaN 19.000 NaN 159.000 159.000 159.000 159.000 159.000 159.000 1.000 1.000 1.000 53.000 53.000 53.000 27.179 27.179 27.179 0.336 0.336 0.336 159.000 159.000 159.000 159.000 159.000 159.000 1.000 1.000 1.000 159.000 159.000 159.000 159.000 159.000 159.000 1.000 1.000 1.000 106.000 106.000 106.000 83.831 83.831 83.831 1.115 1.115 1.115 159.000 159.000 159.000 159.000 159.000 159.000 1.000 1.000 1.000 NaN 0.000 NaN NaN 0.000 NaN -99.995 40.676
4 307 CASH_IN 132937.110 15758521.000 15891458.110 4483044.480 4350107.370 0 12.000 1.000 1.000 1.000 1.000 1.000 132937.110 132937.110 132937.110 132937.110 132937.110 0.006 0.004 0.003 791.292 553.905 433.020 132937.110 132937.110 132937.110 2.000 4.000 11.000 14.000 20.000 274028.130 636635.820 4361568.900 5342497.500 7634442.830 0.065 0.058 0.065 25961.720 22260.406 24867.892 2026968.100 2026968.100 2026968.100 1.000 1.000 1.000 1.000 1.000 132937.110 132937.110 132937.110 132937.110 132937.110 0.006 0.004 0.003 791.292 553.905 433.020 132937.110 132937.110 132937.110 1.000 1.000 1.000 1.000 1.000 132937.110 132937.110 132937.110 132937.110 132937.110 0.006 0.004 0.003 791.292 553.905 433.020 132937.110 132937.110 132937.110 1.000 2.000 5.000 6.000 7.000 132937.110 206632.420 1153758.940 1595502.070 1688833.390 0.030 0.025 0.023 6867.613 6647.925 5501.086 383827.870 441743.130 441743.130 1.000 1.000 1.000 1.000 1.000 132937.110 132937.110 132937.110 132937.110 132937.110 0.006 0.004 0.003 791.292 553.905 433.020 132937.110 132937.110 132937.110 NaN 6.000 NaN NaN 53.000 NaN 168.000 240.000 307.000 168.000 240.000 307.000 1.000 1.000 1.000 30.545 34.286 30.700 10.555 12.310 11.019 0.135 0.135 0.135 168.000 240.000 307.000 168.000 240.000 307.000 1.000 1.000 1.000 168.000 240.000 307.000 168.000 240.000 307.000 1.000 1.000 1.000 33.600 40.000 43.857 19.357 19.997 24.166 0.346 0.301 0.301 168.000 240.000 307.000 168.000 240.000 307.000 1.000 1.000 1.000 NaN 0.000 NaN NaN 0.000 NaN 0.844 -2.965
In [43]:
from sklearn.model_selection import train_test_split
from sklearn.utils import resample
In [44]:
test = model_data[model_data.day >= 26].drop(['day'], axis=1)
test.head()
Out[44]:
step type amount oldbalanceOrg newbalanceOrig oldbalanceDest newbalanceDest isFraud nameOrig_rolling_txn_count_1day nameOrig_rolling_txn_count_3day nameOrig_rolling_txn_count_7day nameOrig_rolling_txn_count_10day nameOrig_rolling_txn_count_14day nameOrig_rolling_txn_sum_1day nameOrig_rolling_txn_sum_3day nameOrig_rolling_txn_sum_7day nameOrig_rolling_txn_sum_10day nameOrig_rolling_txn_sum_14day nameOrig_rolling_txn_count_mean_7day nameOrig_rolling_txn_count_mean_10day nameOrig_rolling_txn_count_mean_14day nameOrig_rolling_txn_amount_mean_7day nameOrig_rolling_txn_amount_mean_10day nameOrig_rolling_txn_amount_mean_14day nameOrig_rolling_txn_amount_max_7day nameOrig_rolling_txn_amount_max_10day nameOrig_rolling_txn_amount_max_14day nameDest_rolling_txn_count_1day nameDest_rolling_txn_count_3day nameDest_rolling_txn_count_7day nameDest_rolling_txn_count_10day nameDest_rolling_txn_count_14day nameDest_rolling_txn_sum_1day nameDest_rolling_txn_sum_3day nameDest_rolling_txn_sum_7day nameDest_rolling_txn_sum_10day nameDest_rolling_txn_sum_14day nameDest_rolling_txn_count_mean_7day nameDest_rolling_txn_count_mean_10day nameDest_rolling_txn_count_mean_14day nameDest_rolling_txn_amount_mean_7day nameDest_rolling_txn_amount_mean_10day nameDest_rolling_txn_amount_mean_14day nameDest_rolling_txn_amount_max_7day nameDest_rolling_txn_amount_max_10day nameDest_rolling_txn_amount_max_14day nameOrig_nameDest_rolling_txn_count_1day nameOrig_nameDest_rolling_txn_count_3day nameOrig_nameDest_rolling_txn_count_7day nameOrig_nameDest_rolling_txn_count_10day nameOrig_nameDest_rolling_txn_count_14day nameOrig_nameDest_rolling_txn_sum_1day nameOrig_nameDest_rolling_txn_sum_3day nameOrig_nameDest_rolling_txn_sum_7day nameOrig_nameDest_rolling_txn_sum_10day nameOrig_nameDest_rolling_txn_sum_14day nameOrig_nameDest_rolling_txn_count_mean_7day nameOrig_nameDest_rolling_txn_count_mean_10day nameOrig_nameDest_rolling_txn_count_mean_14day nameOrig_nameDest_rolling_txn_amount_mean_7day nameOrig_nameDest_rolling_txn_amount_mean_10day nameOrig_nameDest_rolling_txn_amount_mean_14day nameOrig_nameDest_rolling_txn_amount_max_7day nameOrig_nameDest_rolling_txn_amount_max_10day nameOrig_nameDest_rolling_txn_amount_max_14day nameOrig_type_rolling_txn_count_1day nameOrig_type_rolling_txn_count_3day nameOrig_type_rolling_txn_count_7day nameOrig_type_rolling_txn_count_10day nameOrig_type_rolling_txn_count_14day nameOrig_type_rolling_txn_sum_1day nameOrig_type_rolling_txn_sum_3day nameOrig_type_rolling_txn_sum_7day nameOrig_type_rolling_txn_sum_10day nameOrig_type_rolling_txn_sum_14day nameOrig_type_rolling_txn_count_mean_7day nameOrig_type_rolling_txn_count_mean_10day nameOrig_type_rolling_txn_count_mean_14day nameOrig_type_rolling_txn_amount_mean_7day nameOrig_type_rolling_txn_amount_mean_10day nameOrig_type_rolling_txn_amount_mean_14day nameOrig_type_rolling_txn_amount_max_7day nameOrig_type_rolling_txn_amount_max_10day nameOrig_type_rolling_txn_amount_max_14day nameDest_type_rolling_txn_count_1day nameDest_type_rolling_txn_count_3day nameDest_type_rolling_txn_count_7day nameDest_type_rolling_txn_count_10day nameDest_type_rolling_txn_count_14day nameDest_type_rolling_txn_sum_1day nameDest_type_rolling_txn_sum_3day nameDest_type_rolling_txn_sum_7day nameDest_type_rolling_txn_sum_10day nameDest_type_rolling_txn_sum_14day nameDest_type_rolling_txn_count_mean_7day nameDest_type_rolling_txn_count_mean_10day nameDest_type_rolling_txn_count_mean_14day nameDest_type_rolling_txn_amount_mean_7day nameDest_type_rolling_txn_amount_mean_10day nameDest_type_rolling_txn_amount_mean_14day nameDest_type_rolling_txn_amount_max_7day nameDest_type_rolling_txn_amount_max_10day nameDest_type_rolling_txn_amount_max_14day nameOrig_nameDest_type_rolling_txn_count_1day nameOrig_nameDest_type_rolling_txn_count_3day nameOrig_nameDest_type_rolling_txn_count_7day nameOrig_nameDest_type_rolling_txn_count_10day nameOrig_nameDest_type_rolling_txn_count_14day nameOrig_nameDest_type_rolling_txn_sum_1day nameOrig_nameDest_type_rolling_txn_sum_3day nameOrig_nameDest_type_rolling_txn_sum_7day nameOrig_nameDest_type_rolling_txn_sum_10day nameOrig_nameDest_type_rolling_txn_sum_14day nameOrig_nameDest_type_rolling_txn_count_mean_7day nameOrig_nameDest_type_rolling_txn_count_mean_10day nameOrig_nameDest_type_rolling_txn_count_mean_14day nameOrig_nameDest_type_rolling_txn_amount_mean_7day nameOrig_nameDest_type_rolling_txn_amount_mean_10day nameOrig_nameDest_type_rolling_txn_amount_mean_14day nameOrig_nameDest_type_rolling_txn_amount_max_7day nameOrig_nameDest_type_rolling_txn_amount_max_10day nameOrig_nameDest_type_rolling_txn_amount_max_14day nameOrig_time_since_last_txn nameDest_time_since_last_txn nameOrig_nameDest_time_since_last_txn nameOrig_type_time_since_last_txn nameDest_type_time_since_last_txn nameOrig_nameDest_type_time_since_last_txn nameOrig_txnCount_velocity_ratio_over_7day nameOrig_txnCount_velocity_ratio_over_10day nameOrig_txnCount_velocity_ratio_over_14day nameOrig_amount_velocity_ratio_over_7day nameOrig_amount_velocity_ratio_over_10day nameOrig_amount_velocity_ratio_over_14day nameOrig_amount_max_velocity_ratio_over_7day nameOrig_amount_max_velocity_ratio_over_10day nameOrig_amount_max_velocity_ratio_over_14day nameDest_txnCount_velocity_ratio_over_7day nameDest_txnCount_velocity_ratio_over_10day nameDest_txnCount_velocity_ratio_over_14day nameDest_amount_velocity_ratio_over_7day nameDest_amount_velocity_ratio_over_10day nameDest_amount_velocity_ratio_over_14day nameDest_amount_max_velocity_ratio_over_7day nameDest_amount_max_velocity_ratio_over_10day nameDest_amount_max_velocity_ratio_over_14day nameOrig_nameDest_txnCount_velocity_ratio_over_7day nameOrig_nameDest_txnCount_velocity_ratio_over_10day nameOrig_nameDest_txnCount_velocity_ratio_over_14day nameOrig_nameDest_amount_velocity_ratio_over_7day nameOrig_nameDest_amount_velocity_ratio_over_10day nameOrig_nameDest_amount_velocity_ratio_over_14day nameOrig_nameDest_amount_max_velocity_ratio_over_7day nameOrig_nameDest_amount_max_velocity_ratio_over_10day nameOrig_nameDest_amount_max_velocity_ratio_over_14day nameOrig_type_txnCount_velocity_ratio_over_7day nameOrig_type_txnCount_velocity_ratio_over_10day nameOrig_type_txnCount_velocity_ratio_over_14day nameOrig_type_amount_velocity_ratio_over_7day nameOrig_type_amount_velocity_ratio_over_10day nameOrig_type_amount_velocity_ratio_over_14day nameOrig_type_amount_max_velocity_ratio_over_7day nameOrig_type_amount_max_velocity_ratio_over_10day nameOrig_type_amount_max_velocity_ratio_over_14day nameDest_type_txnCount_velocity_ratio_over_7day nameDest_type_txnCount_velocity_ratio_over_10day nameDest_type_txnCount_velocity_ratio_over_14day nameDest_type_amount_velocity_ratio_over_7day nameDest_type_amount_velocity_ratio_over_10day nameDest_type_amount_velocity_ratio_over_14day nameDest_type_amount_max_velocity_ratio_over_7day nameDest_type_amount_max_velocity_ratio_over_10day nameDest_type_amount_max_velocity_ratio_over_14day nameOrig_nameDest_type_txnCount_velocity_ratio_over_7day nameOrig_nameDest_type_txnCount_velocity_ratio_over_10day nameOrig_nameDest_type_txnCount_velocity_ratio_over_14day nameOrig_nameDest_type_amount_velocity_ratio_over_7day nameOrig_nameDest_type_amount_velocity_ratio_over_10day nameOrig_nameDest_type_amount_velocity_ratio_over_14day nameOrig_nameDest_type_amount_max_velocity_ratio_over_7day nameOrig_nameDest_type_amount_max_velocity_ratio_over_10day nameOrig_nameDest_type_amount_max_velocity_ratio_over_14day nameOrig_had_prev_fraud nameDest_had_prev_fraud nameOrig_nameDest_had_prev_fraud nameOrig_type_had_prev_fraud nameDest_type_had_prev_fraud nameOrig_nameDest_type_had_prev_fraud changeBalanceOrg_prcnt changeBalanceDest_prcnt
17 694 TRANSFER 67277.540 204160.000 136882.460 457734.560 525012.100 0 1.000 1.000 1.000 1.000 1.000 67277.540 67277.540 67277.540 67277.540 67277.540 0.006 0.004 0.003 400.462 280.323 200.231 67277.540 67277.540 67277.540 1.000 2.000 2.000 2.000 2.000 67277.540 130533.950 130533.950 130533.950 130533.950 0.012 0.008 0.006 776.988 543.891 388.494 67277.540 67277.540 67277.540 1.000 1.000 1.000 1.000 1.000 67277.540 67277.540 67277.540 67277.540 67277.540 0.006 0.004 0.003 400.462 280.323 200.231 67277.540 67277.540 67277.540 1.000 1.000 1.000 1.000 1.000 67277.540 67277.540 67277.540 67277.540 67277.540 0.006 0.004 0.003 400.462 280.323 200.231 67277.540 67277.540 67277.540 1.000 1.000 1.000 1.000 1.000 67277.540 67277.540 67277.540 67277.540 67277.540 0.006 0.004 0.003 400.462 280.323 200.231 67277.540 67277.540 67277.540 1.000 1.000 1.000 1.000 1.000 67277.540 67277.540 67277.540 67277.540 67277.540 0.006 0.004 0.003 400.462 280.323 200.231 67277.540 67277.540 67277.540 NaN 45.000 NaN NaN 393.000 NaN 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 84.000 120.000 168.000 86.588 123.697 173.175 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 NaN 0.000 NaN NaN 0.000 NaN -32.953 14.698
150 691 CASH_OUT 16508.840 0.000 0.000 938660.930 955169.770 0 1.000 1.000 1.000 1.000 1.000 16508.840 16508.840 16508.840 16508.840 16508.840 0.006 0.004 0.003 98.267 68.787 49.133 16508.840 16508.840 16508.840 1.000 1.000 1.000 1.000 1.000 16508.840 16508.840 16508.840 16508.840 16508.840 0.006 0.004 0.003 98.267 68.787 49.133 16508.840 16508.840 16508.840 1.000 1.000 1.000 1.000 1.000 16508.840 16508.840 16508.840 16508.840 16508.840 0.006 0.004 0.003 98.267 68.787 49.133 16508.840 16508.840 16508.840 1.000 1.000 1.000 1.000 1.000 16508.840 16508.840 16508.840 16508.840 16508.840 0.006 0.004 0.003 98.267 68.787 49.133 16508.840 16508.840 16508.840 1.000 1.000 1.000 1.000 1.000 16508.840 16508.840 16508.840 16508.840 16508.840 0.006 0.004 0.003 98.267 68.787 49.133 16508.840 16508.840 16508.840 1.000 1.000 1.000 1.000 1.000 16508.840 16508.840 16508.840 16508.840 16508.840 0.006 0.004 0.003 98.267 68.787 49.133 16508.840 16508.840 16508.840 NaN 364.000 NaN NaN 456.000 NaN 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 NaN 0.000 NaN NaN 0.000 NaN 0.000 1.759
169 686 TRANSFER 493790.130 0.000 0.000 623627.870 1117418.000 0 1.000 1.000 1.000 1.000 1.000 493790.130 493790.130 493790.130 493790.130 493790.130 0.006 0.004 0.003 2939.227 2057.459 1469.613 493790.130 493790.130 493790.130 1.000 1.000 1.000 1.000 4.000 493790.130 493790.130 493790.130 493790.130 1171692.630 0.006 0.004 0.012 2939.227 2057.459 3487.180 493790.130 493790.130 493790.130 1.000 1.000 1.000 1.000 1.000 493790.130 493790.130 493790.130 493790.130 493790.130 0.006 0.004 0.003 2939.227 2057.459 1469.613 493790.130 493790.130 493790.130 1.000 1.000 1.000 1.000 1.000 493790.130 493790.130 493790.130 493790.130 493790.130 0.006 0.004 0.003 2939.227 2057.459 1469.613 493790.130 493790.130 493790.130 1.000 1.000 1.000 1.000 2.000 493790.130 493790.130 493790.130 493790.130 706914.820 0.006 0.004 0.006 2939.227 2057.459 2103.913 493790.130 493790.130 493790.130 1.000 1.000 1.000 1.000 1.000 493790.130 493790.130 493790.130 493790.130 493790.130 0.006 0.004 0.003 2939.227 2057.459 1469.613 493790.130 493790.130 493790.130 NaN 290.000 NaN NaN 309.000 NaN 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 84.000 168.000 240.000 141.602 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 168.000 168.000 240.000 234.701 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 NaN 0.000 NaN NaN 0.000 NaN 0.000 79.180
235 640 CASH_OUT 382268.420 0.000 0.000 13323843.460 13706111.880 0 1.000 1.000 1.000 1.000 1.000 382268.420 382268.420 382268.420 382268.420 382268.420 0.006 0.004 0.003 2275.407 1592.785 1137.704 382268.420 382268.420 382268.420 1.000 1.000 1.000 1.000 5.000 382268.420 382268.420 382268.420 382268.420 7591876.780 0.006 0.004 0.015 2275.407 1592.785 22594.871 382268.420 382268.420 4048890.050 1.000 1.000 1.000 1.000 1.000 382268.420 382268.420 382268.420 382268.420 382268.420 0.006 0.004 0.003 2275.407 1592.785 1137.704 382268.420 382268.420 382268.420 1.000 1.000 1.000 1.000 1.000 382268.420 382268.420 382268.420 382268.420 382268.420 0.006 0.004 0.003 2275.407 1592.785 1137.704 382268.420 382268.420 382268.420 1.000 1.000 1.000 1.000 2.000 382268.420 382268.420 382268.420 382268.420 653703.110 0.006 0.004 0.006 2275.407 1592.785 1945.545 382268.420 382268.420 382268.420 1.000 1.000 1.000 1.000 1.000 382268.420 382268.420 382268.420 382268.420 382268.420 0.006 0.004 0.003 2275.407 1592.785 1137.704 382268.420 382268.420 382268.420 NaN 241.000 NaN NaN 241.000 NaN 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 67.200 168.000 240.000 16.918 1.000 1.000 0.094 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 168.000 168.000 240.000 196.484 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 NaN 0.000 NaN NaN 0.000 NaN 0.000 2.869
254 715 DEBIT 2737.510 2720.000 0.000 32886.520 35624.030 0 1.000 1.000 1.000 1.000 1.000 2737.510 2737.510 2737.510 2737.510 2737.510 0.006 0.004 0.003 16.295 11.406 8.147 2737.510 2737.510 2737.510 1.000 1.000 1.000 1.000 2.000 2737.510 2737.510 2737.510 2737.510 35624.030 0.006 0.004 0.006 16.295 11.406 106.024 2737.510 2737.510 32886.520 1.000 1.000 1.000 1.000 1.000 2737.510 2737.510 2737.510 2737.510 2737.510 0.006 0.004 0.003 16.295 11.406 8.147 2737.510 2737.510 2737.510 1.000 1.000 1.000 1.000 1.000 2737.510 2737.510 2737.510 2737.510 2737.510 0.006 0.004 0.003 16.295 11.406 8.147 2737.510 2737.510 2737.510 1.000 1.000 1.000 1.000 1.000 2737.510 2737.510 2737.510 2737.510 2737.510 0.006 0.004 0.003 16.295 11.406 8.147 2737.510 2737.510 2737.510 1.000 1.000 1.000 1.000 1.000 2737.510 2737.510 2737.510 2737.510 2737.510 0.006 0.004 0.003 16.295 11.406 8.147 2737.510 2737.510 2737.510 NaN 318.000 NaN NaN NaN NaN 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 168.000 168.000 240.000 25.820 1.000 1.000 0.083 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 NaN 0.000 NaN NaN NaN NaN -99.963 8.324
In [45]:
print(test.shape)
print(test.groupby(['isFraud'])['isFraud'].count())

(1375, 190)
isFraud
0    1341
1      34
Name: isFraud, dtype: int64
In [46]:
#validation = model_data[(model_data.day >= 21) & (model_data.day < 26)].drop(['day'], axis=1)
#validation.head()
In [47]:
train = model_data[model_data.day < 26].drop(['day'], axis=1)
train.head()
Out[47]:
step type amount oldbalanceOrg newbalanceOrig oldbalanceDest newbalanceDest isFraud nameOrig_rolling_txn_count_1day nameOrig_rolling_txn_count_3day nameOrig_rolling_txn_count_7day nameOrig_rolling_txn_count_10day nameOrig_rolling_txn_count_14day nameOrig_rolling_txn_sum_1day nameOrig_rolling_txn_sum_3day nameOrig_rolling_txn_sum_7day nameOrig_rolling_txn_sum_10day nameOrig_rolling_txn_sum_14day nameOrig_rolling_txn_count_mean_7day nameOrig_rolling_txn_count_mean_10day nameOrig_rolling_txn_count_mean_14day nameOrig_rolling_txn_amount_mean_7day nameOrig_rolling_txn_amount_mean_10day nameOrig_rolling_txn_amount_mean_14day nameOrig_rolling_txn_amount_max_7day nameOrig_rolling_txn_amount_max_10day nameOrig_rolling_txn_amount_max_14day nameDest_rolling_txn_count_1day nameDest_rolling_txn_count_3day nameDest_rolling_txn_count_7day nameDest_rolling_txn_count_10day nameDest_rolling_txn_count_14day nameDest_rolling_txn_sum_1day nameDest_rolling_txn_sum_3day nameDest_rolling_txn_sum_7day nameDest_rolling_txn_sum_10day nameDest_rolling_txn_sum_14day nameDest_rolling_txn_count_mean_7day nameDest_rolling_txn_count_mean_10day nameDest_rolling_txn_count_mean_14day nameDest_rolling_txn_amount_mean_7day nameDest_rolling_txn_amount_mean_10day nameDest_rolling_txn_amount_mean_14day nameDest_rolling_txn_amount_max_7day nameDest_rolling_txn_amount_max_10day nameDest_rolling_txn_amount_max_14day nameOrig_nameDest_rolling_txn_count_1day nameOrig_nameDest_rolling_txn_count_3day nameOrig_nameDest_rolling_txn_count_7day nameOrig_nameDest_rolling_txn_count_10day nameOrig_nameDest_rolling_txn_count_14day nameOrig_nameDest_rolling_txn_sum_1day nameOrig_nameDest_rolling_txn_sum_3day nameOrig_nameDest_rolling_txn_sum_7day nameOrig_nameDest_rolling_txn_sum_10day nameOrig_nameDest_rolling_txn_sum_14day nameOrig_nameDest_rolling_txn_count_mean_7day nameOrig_nameDest_rolling_txn_count_mean_10day nameOrig_nameDest_rolling_txn_count_mean_14day nameOrig_nameDest_rolling_txn_amount_mean_7day nameOrig_nameDest_rolling_txn_amount_mean_10day nameOrig_nameDest_rolling_txn_amount_mean_14day nameOrig_nameDest_rolling_txn_amount_max_7day nameOrig_nameDest_rolling_txn_amount_max_10day nameOrig_nameDest_rolling_txn_amount_max_14day nameOrig_type_rolling_txn_count_1day nameOrig_type_rolling_txn_count_3day nameOrig_type_rolling_txn_count_7day nameOrig_type_rolling_txn_count_10day nameOrig_type_rolling_txn_count_14day nameOrig_type_rolling_txn_sum_1day nameOrig_type_rolling_txn_sum_3day nameOrig_type_rolling_txn_sum_7day nameOrig_type_rolling_txn_sum_10day nameOrig_type_rolling_txn_sum_14day nameOrig_type_rolling_txn_count_mean_7day nameOrig_type_rolling_txn_count_mean_10day nameOrig_type_rolling_txn_count_mean_14day nameOrig_type_rolling_txn_amount_mean_7day nameOrig_type_rolling_txn_amount_mean_10day nameOrig_type_rolling_txn_amount_mean_14day nameOrig_type_rolling_txn_amount_max_7day nameOrig_type_rolling_txn_amount_max_10day nameOrig_type_rolling_txn_amount_max_14day nameDest_type_rolling_txn_count_1day nameDest_type_rolling_txn_count_3day nameDest_type_rolling_txn_count_7day nameDest_type_rolling_txn_count_10day nameDest_type_rolling_txn_count_14day nameDest_type_rolling_txn_sum_1day nameDest_type_rolling_txn_sum_3day nameDest_type_rolling_txn_sum_7day nameDest_type_rolling_txn_sum_10day nameDest_type_rolling_txn_sum_14day nameDest_type_rolling_txn_count_mean_7day nameDest_type_rolling_txn_count_mean_10day nameDest_type_rolling_txn_count_mean_14day nameDest_type_rolling_txn_amount_mean_7day nameDest_type_rolling_txn_amount_mean_10day nameDest_type_rolling_txn_amount_mean_14day nameDest_type_rolling_txn_amount_max_7day nameDest_type_rolling_txn_amount_max_10day nameDest_type_rolling_txn_amount_max_14day nameOrig_nameDest_type_rolling_txn_count_1day nameOrig_nameDest_type_rolling_txn_count_3day nameOrig_nameDest_type_rolling_txn_count_7day nameOrig_nameDest_type_rolling_txn_count_10day nameOrig_nameDest_type_rolling_txn_count_14day nameOrig_nameDest_type_rolling_txn_sum_1day nameOrig_nameDest_type_rolling_txn_sum_3day nameOrig_nameDest_type_rolling_txn_sum_7day nameOrig_nameDest_type_rolling_txn_sum_10day nameOrig_nameDest_type_rolling_txn_sum_14day nameOrig_nameDest_type_rolling_txn_count_mean_7day nameOrig_nameDest_type_rolling_txn_count_mean_10day nameOrig_nameDest_type_rolling_txn_count_mean_14day nameOrig_nameDest_type_rolling_txn_amount_mean_7day nameOrig_nameDest_type_rolling_txn_amount_mean_10day nameOrig_nameDest_type_rolling_txn_amount_mean_14day nameOrig_nameDest_type_rolling_txn_amount_max_7day nameOrig_nameDest_type_rolling_txn_amount_max_10day nameOrig_nameDest_type_rolling_txn_amount_max_14day nameOrig_time_since_last_txn nameDest_time_since_last_txn nameOrig_nameDest_time_since_last_txn nameOrig_type_time_since_last_txn nameDest_type_time_since_last_txn nameOrig_nameDest_type_time_since_last_txn nameOrig_txnCount_velocity_ratio_over_7day nameOrig_txnCount_velocity_ratio_over_10day nameOrig_txnCount_velocity_ratio_over_14day nameOrig_amount_velocity_ratio_over_7day nameOrig_amount_velocity_ratio_over_10day nameOrig_amount_velocity_ratio_over_14day nameOrig_amount_max_velocity_ratio_over_7day nameOrig_amount_max_velocity_ratio_over_10day nameOrig_amount_max_velocity_ratio_over_14day nameDest_txnCount_velocity_ratio_over_7day nameDest_txnCount_velocity_ratio_over_10day nameDest_txnCount_velocity_ratio_over_14day nameDest_amount_velocity_ratio_over_7day nameDest_amount_velocity_ratio_over_10day nameDest_amount_velocity_ratio_over_14day nameDest_amount_max_velocity_ratio_over_7day nameDest_amount_max_velocity_ratio_over_10day nameDest_amount_max_velocity_ratio_over_14day nameOrig_nameDest_txnCount_velocity_ratio_over_7day nameOrig_nameDest_txnCount_velocity_ratio_over_10day nameOrig_nameDest_txnCount_velocity_ratio_over_14day nameOrig_nameDest_amount_velocity_ratio_over_7day nameOrig_nameDest_amount_velocity_ratio_over_10day nameOrig_nameDest_amount_velocity_ratio_over_14day nameOrig_nameDest_amount_max_velocity_ratio_over_7day nameOrig_nameDest_amount_max_velocity_ratio_over_10day nameOrig_nameDest_amount_max_velocity_ratio_over_14day nameOrig_type_txnCount_velocity_ratio_over_7day nameOrig_type_txnCount_velocity_ratio_over_10day nameOrig_type_txnCount_velocity_ratio_over_14day nameOrig_type_amount_velocity_ratio_over_7day nameOrig_type_amount_velocity_ratio_over_10day nameOrig_type_amount_velocity_ratio_over_14day nameOrig_type_amount_max_velocity_ratio_over_7day nameOrig_type_amount_max_velocity_ratio_over_10day nameOrig_type_amount_max_velocity_ratio_over_14day nameDest_type_txnCount_velocity_ratio_over_7day nameDest_type_txnCount_velocity_ratio_over_10day nameDest_type_txnCount_velocity_ratio_over_14day nameDest_type_amount_velocity_ratio_over_7day nameDest_type_amount_velocity_ratio_over_10day nameDest_type_amount_velocity_ratio_over_14day nameDest_type_amount_max_velocity_ratio_over_7day nameDest_type_amount_max_velocity_ratio_over_10day nameDest_type_amount_max_velocity_ratio_over_14day nameOrig_nameDest_type_txnCount_velocity_ratio_over_7day nameOrig_nameDest_type_txnCount_velocity_ratio_over_10day nameOrig_nameDest_type_txnCount_velocity_ratio_over_14day nameOrig_nameDest_type_amount_velocity_ratio_over_7day nameOrig_nameDest_type_amount_velocity_ratio_over_10day nameOrig_nameDest_type_amount_velocity_ratio_over_14day nameOrig_nameDest_type_amount_max_velocity_ratio_over_7day nameOrig_nameDest_type_amount_max_velocity_ratio_over_10day nameOrig_nameDest_type_amount_max_velocity_ratio_over_14day nameOrig_had_prev_fraud nameDest_had_prev_fraud nameOrig_nameDest_had_prev_fraud nameOrig_type_had_prev_fraud nameDest_type_had_prev_fraud nameOrig_nameDest_type_had_prev_fraud changeBalanceOrg_prcnt changeBalanceDest_prcnt
0 289 CASH_IN 223513.230 2911285.730 3134798.970 482434.060 258920.820 0 1.000 1.000 1.000 1.000 1.000 223513.230 223513.230 223513.230 223513.230 223513.230 0.006 0.004 0.003 1330.436 931.305 773.402 223513.230 223513.230 223513.230 3.000 3.000 5.000 5.000 5.000 321996.020 321996.020 1240916.250 1240916.250 1240916.250 0.030 0.021 0.017 7386.406 5170.484 4293.828 743924.160 743924.160 743924.160 1.000 1.000 1.000 1.000 1.000 223513.230 223513.230 223513.230 223513.230 223513.230 0.006 0.004 0.003 1330.436 931.305 773.402 223513.230 223513.230 223513.230 1.000 1.000 1.000 1.000 1.000 223513.230 223513.230 223513.230 223513.230 223513.230 0.006 0.004 0.003 1330.436 931.305 773.402 223513.230 223513.230 223513.230 2.000 2.000 3.000 3.000 3.000 316001.640 316001.640 490997.710 490997.710 490997.710 0.018 0.013 0.010 2922.605 2045.824 1698.954 223513.230 223513.230 223513.230 1.000 1.000 1.000 1.000 1.000 223513.230 223513.230 223513.230 223513.230 223513.230 0.006 0.004 0.003 1330.436 931.305 773.402 223513.230 223513.230 223513.230 NaN 5.000 NaN NaN 5.000 NaN 168.000 240.000 289.000 168.000 240.000 289.000 1.000 1.000 1.000 100.800 144.000 173.400 43.593 62.276 74.990 0.433 0.433 0.433 168.000 240.000 289.000 168.000 240.000 289.000 1.000 1.000 1.000 168.000 240.000 289.000 168.000 240.000 289.000 1.000 1.000 1.000 112.000 160.000 192.667 108.123 154.462 185.998 1.414 1.414 1.414 168.000 240.000 289.000 168.000 240.000 289.000 1.000 1.000 1.000 NaN 0.000 NaN NaN 0.000 NaN 7.677 -46.330
1 259 CASH_OUT 163976.410 0.000 0.000 2281442.130 2445418.540 0 1.000 1.000 1.000 1.000 1.000 163976.410 163976.410 163976.410 163976.410 163976.410 0.006 0.004 0.004 976.050 683.235 633.114 163976.410 163976.410 163976.410 1.000 4.000 8.000 12.000 12.000 163976.410 1101733.320 2208005.030 3036206.260 3036206.260 0.048 0.050 0.046 13142.887 12650.859 11722.804 787971.490 787971.490 787971.490 1.000 1.000 1.000 1.000 1.000 163976.410 163976.410 163976.410 163976.410 163976.410 0.006 0.004 0.004 976.050 683.235 633.114 163976.410 163976.410 163976.410 1.000 1.000 1.000 1.000 1.000 163976.410 163976.410 163976.410 163976.410 163976.410 0.006 0.004 0.004 976.050 683.235 633.114 163976.410 163976.410 163976.410 1.000 3.000 3.000 5.000 5.000 163976.410 810348.570 810348.570 1209945.550 1209945.550 0.018 0.021 0.019 4823.503 5041.440 4671.604 411102.030 411102.030 411102.030 1.000 1.000 1.000 1.000 1.000 163976.410 163976.410 163976.410 163976.410 163976.410 0.006 0.004 0.004 976.050 683.235 633.114 163976.410 163976.410 163976.410 NaN 24.000 NaN NaN 24.000 NaN 168.000 240.000 259.000 168.000 240.000 259.000 1.000 1.000 1.000 21.000 20.000 21.583 12.476 12.962 13.988 0.208 0.208 0.208 168.000 240.000 259.000 168.000 240.000 259.000 1.000 1.000 1.000 168.000 240.000 259.000 168.000 240.000 259.000 1.000 1.000 1.000 56.000 48.000 51.800 33.995 32.526 35.101 0.399 0.399 0.399 168.000 240.000 259.000 168.000 240.000 259.000 1.000 1.000 1.000 NaN 0.000 NaN NaN 0.000 NaN 0.000 7.187
2 353 CASH_IN 71801.780 327251.000 399052.780 321931.140 250129.350 0 1.000 1.000 1.000 1.000 1.000 71801.780 71801.780 71801.780 71801.780 71801.780 0.006 0.004 0.003 427.392 299.174 213.696 71801.780 71801.780 71801.780 1.000 2.000 3.000 3.000 3.000 71801.780 154655.900 393732.920 393732.920 393732.920 0.018 0.013 0.009 2343.648 1640.554 1171.824 239077.020 239077.020 239077.020 1.000 1.000 1.000 1.000 1.000 71801.780 71801.780 71801.780 71801.780 71801.780 0.006 0.004 0.003 427.392 299.174 213.696 71801.780 71801.780 71801.780 1.000 1.000 1.000 1.000 1.000 71801.780 71801.780 71801.780 71801.780 71801.780 0.006 0.004 0.003 427.392 299.174 213.696 71801.780 71801.780 71801.780 1.000 1.000 1.000 1.000 1.000 71801.780 71801.780 71801.780 71801.780 71801.780 0.006 0.004 0.003 427.392 299.174 213.696 71801.780 71801.780 71801.780 1.000 1.000 1.000 1.000 1.000 71801.780 71801.780 71801.780 71801.780 71801.780 0.006 0.004 0.003 427.392 299.174 213.696 71801.780 71801.780 71801.780 NaN 24.000 NaN NaN NaN NaN 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 56.000 80.000 112.000 30.637 43.767 61.274 0.300 0.300 0.300 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 NaN 0.000 NaN NaN 0.000 NaN 21.941 -22.303
3 159 CASH_OUT 377853.580 20791.000 0.000 1846032.140 2596929.660 0 1.000 1.000 1.000 1.000 1.000 377853.580 377853.580 377853.580 377853.580 377853.580 0.006 0.006 0.006 2376.438 2376.438 2376.438 377853.580 377853.580 377853.580 2.000 4.000 6.000 6.000 6.000 456275.200 2223885.720 2669216.740 2669216.740 2669216.740 0.038 0.038 0.038 16787.527 16787.527 16787.527 1358478.670 1358478.670 1358478.670 1.000 1.000 1.000 1.000 1.000 377853.580 377853.580 377853.580 377853.580 377853.580 0.006 0.006 0.006 2376.438 2376.438 2376.438 377853.580 377853.580 377853.580 1.000 1.000 1.000 1.000 1.000 377853.580 377853.580 377853.580 377853.580 377853.580 0.006 0.006 0.006 2376.438 2376.438 2376.438 377853.580 377853.580 377853.580 2.000 3.000 3.000 3.000 3.000 456275.200 865407.050 865407.050 865407.050 865407.050 0.019 0.019 0.019 5442.812 5442.812 5442.812 409131.850 409131.850 409131.850 1.000 1.000 1.000 1.000 1.000 377853.580 377853.580 377853.580 377853.580 377853.580 0.006 0.006 0.006 2376.438 2376.438 2376.438 377853.580 377853.580 377853.580 NaN 19.000 NaN NaN 19.000 NaN 159.000 159.000 159.000 159.000 159.000 159.000 1.000 1.000 1.000 53.000 53.000 53.000 27.179 27.179 27.179 0.336 0.336 0.336 159.000 159.000 159.000 159.000 159.000 159.000 1.000 1.000 1.000 159.000 159.000 159.000 159.000 159.000 159.000 1.000 1.000 1.000 106.000 106.000 106.000 83.831 83.831 83.831 1.115 1.115 1.115 159.000 159.000 159.000 159.000 159.000 159.000 1.000 1.000 1.000 NaN 0.000 NaN NaN 0.000 NaN -99.995 40.676
4 307 CASH_IN 132937.110 15758521.000 15891458.110 4483044.480 4350107.370 0 1.000 1.000 1.000 1.000 1.000 132937.110 132937.110 132937.110 132937.110 132937.110 0.006 0.004 0.003 791.292 553.905 433.020 132937.110 132937.110 132937.110 2.000 4.000 11.000 14.000 20.000 274028.130 636635.820 4361568.900 5342497.500 7634442.830 0.065 0.058 0.065 25961.720 22260.406 24867.892 2026968.100 2026968.100 2026968.100 1.000 1.000 1.000 1.000 1.000 132937.110 132937.110 132937.110 132937.110 132937.110 0.006 0.004 0.003 791.292 553.905 433.020 132937.110 132937.110 132937.110 1.000 1.000 1.000 1.000 1.000 132937.110 132937.110 132937.110 132937.110 132937.110 0.006 0.004 0.003 791.292 553.905 433.020 132937.110 132937.110 132937.110 1.000 2.000 5.000 6.000 7.000 132937.110 206632.420 1153758.940 1595502.070 1688833.390 0.030 0.025 0.023 6867.613 6647.925 5501.086 383827.870 441743.130 441743.130 1.000 1.000 1.000 1.000 1.000 132937.110 132937.110 132937.110 132937.110 132937.110 0.006 0.004 0.003 791.292 553.905 433.020 132937.110 132937.110 132937.110 NaN 6.000 NaN NaN 53.000 NaN 168.000 240.000 307.000 168.000 240.000 307.000 1.000 1.000 1.000 30.545 34.286 30.700 10.555 12.310 11.019 0.135 0.135 0.135 168.000 240.000 307.000 168.000 240.000 307.000 1.000 1.000 1.000 168.000 240.000 307.000 168.000 240.000 307.000 1.000 1.000 1.000 33.600 40.000 43.857 19.357 19.997 24.166 0.346 0.301 0.301 168.000 240.000 307.000 168.000 240.000 307.000 1.000 1.000 1.000 NaN 0.000 NaN NaN 0.000 NaN 0.844 -2.965
In [48]:
print(train.shape)
print(train.groupby(['isFraud'])['isFraud'].count())

(98625, 190)
isFraud
0    98463
1      162
Name: isFraud, dtype: int64

6. Model Pipeline¶

In [49]:
from sklearn.impute import SimpleImputer
from sklearn.preprocessing import OneHotEncoder, MinMaxScaler
from sklearn.pipeline import Pipeline
from sklearn.compose import ColumnTransformer
from sklearn.feature_selection import SelectFromModel

6.1 Numerical Featurees¶

In [50]:
numeric_pipeline = Pipeline(steps=[
    ('impute', SimpleImputer(strategy='mean')) #,('scale', MinMaxScaler())
])

6.2 Categorical Features¶

In [51]:
categorical_pipeline = Pipeline(steps=[
    ('impute', SimpleImputer(strategy='most_frequent')),
    ('one-hot', OneHotEncoder(handle_unknown='ignore', sparse=False))
])

6.3 Full Feature Processor¶

In [52]:
numerical_features = train.drop(['step','isFraud','type'], axis=1).columns
categorical_features = ['type']
In [53]:
full_processor = ColumnTransformer(transformers=[
    ('number', numeric_pipeline, numerical_features),
    ('category', categorical_pipeline, categorical_features)
])

6.4 Complete Model Pipeline¶

In [54]:
threshold = 0.5
xgb_model_V1 = xgboost.XGBClassifier(subsample=0.8, max_depth=15, learning_rate=0.3, objective= 'binary:logistic',n_jobs=-1,verbosity = 0)
xgb_pipeline_V1 = Pipeline(steps=[('preprocess', full_processor), ('feature_selection', SelectFromModel(xgboost.XGBClassifier())), ('model', xgb_model_V1)])

xgb_model_V2 = xgboost.XGBClassifier(subsample=0.85, max_depth=15, learning_rate=0.3, objective= 'binary:logistic',n_jobs=-1,verbosity = 0)
xgb_pipeline_V2 = Pipeline(steps=[('preprocess', full_processor), ('feature_selection', SelectFromModel(xgboost.XGBClassifier())), ('model', xgb_model_V2)])

xgb_model_V3 = xgboost.XGBClassifier(subsample=0.9, max_depth=15, learning_rate=0.3, objective= 'binary:logistic',n_jobs=-1,verbosity = 0)
xgb_pipeline_V3 = Pipeline(steps=[('preprocess', full_processor), ('feature_selection', SelectFromModel(xgboost.XGBClassifier())), ('model', xgb_model_V3)])

xgb_model_V4 = xgboost.XGBClassifier(subsample=1.0, max_depth=15, learning_rate=0.3, objective= 'binary:logistic',n_jobs=-1,verbosity = 0)
xgb_pipeline_V4 = Pipeline(steps=[('preprocess', full_processor), ('feature_selection', SelectFromModel(xgboost.XGBClassifier())), ('model', xgb_model_V4)])

7. Model Selection¶

7.1 Rolling-window Cross-validation on Original Train Set¶

In [55]:
X = train.drop(['step','isFraud'], axis=1).fillna(0)
y = train[['isFraud']]

print('Total instances', len(y))
print('Total positive instances', np.sum(y.values))

from sklearn.model_selection import TimeSeriesSplit
tscv = TimeSeriesSplit(n_splits=5)

print(tscv)

time_split_cv_result = pd.DataFrame(columns = ['Iterations', 'Model', 'Recall', 'Fscore'])

i = 0
for train_index, test_index in tscv.split(X):
    i += 1
    
    print("TRAIN:", train_index, "TEST:", test_index)
    X_train, X_test = X.iloc[train_index], X.iloc[test_index]
    y_train, y_test = y.iloc[train_index], y.iloc[test_index]
    
    xgb_pipeline_V1.fit(X_train, y_train)
    xgb_V1_recall = recall_score(y_test, xgb_pipeline_V1.predict(X_test))
    xgb_V1_fscore = f1_score(y_test, xgb_pipeline_V1.predict(X_test))
    
    time_split_cv_result = pd.concat([time_split_cv_result, pd.DataFrame([{'Iteration' : i, 
                                                                            'Model' : 'xgb_V1', 
                                                                            'Recall' : xgb_V1_recall, 
                                                                            'Fscore' : xgb_V1_fscore}])])
    
    xgb_pipeline_V2.fit(X_train, y_train)
    xgb_V2_recall = recall_score(y_test, xgb_pipeline_V2.predict(X_test))
    xgb_V2_fscore = f1_score(y_test, xgb_pipeline_V2.predict(X_test))
    
    time_split_cv_result = pd.concat([time_split_cv_result, pd.DataFrame([{'Iteration' : i, 
                                                                            'Model' : 'xgb_V2', 
                                                                            'Recall' : xgb_V2_recall, 
                                                                            'Fscore' : xgb_V2_fscore}])])
                                                                           
    xgb_pipeline_V3.fit(X_train, y_train)
    xgb_V3_recall = recall_score(y_test, xgb_pipeline_V3.predict(X_test))
    xgb_V3_fscore = f1_score(y_test, xgb_pipeline_V3.predict(X_test))
    
    time_split_cv_result = pd.concat([time_split_cv_result, pd.DataFrame([{'Iteration' : i, 
                                                                            'Model' : 'xgb_V3', 
                                                                            'Recall' : xgb_V3_recall, 
                                                                            'Fscore' : xgb_V3_fscore}])])
                                                                           
    xgb_pipeline_V4.fit(X_train, y_train)
    xgb_V4_recall = recall_score(y_test, xgb_pipeline_V4.predict(X_test))
    xgb_V4_fscore = f1_score(y_test, xgb_pipeline_V4.predict(X_test))
    
    time_split_cv_result = pd.concat([time_split_cv_result, pd.DataFrame([{'Iteration' : i, 
                                                                            'Model' : 'xgb_V4', 
                                                                            'Recall' : xgb_V4_recall, 
                                                                            'Fscore' : xgb_V4_fscore}])])

time_split_cv_result.groupby(['Model'], as_index=False) \
                .agg({'Iteration':['count'], 'Recall':['mean','std'], 'Fscore':['mean','std']}) \
                .reset_index(drop=True)

Total instances 98625
Total positive instances 162
TimeSeriesSplit(gap=0, max_train_size=None, n_splits=5, test_size=None)
TRAIN: [    0     1     2 ... 16437 16438 16439] TEST: [16440 16441 16442 ... 32874 32875 32876]
TRAIN: [    0     1     2 ... 32874 32875 32876] TEST: [32877 32878 32879 ... 49311 49312 49313]
TRAIN: [    0     1     2 ... 49311 49312 49313] TEST: [49314 49315 49316 ... 65748 65749 65750]
TRAIN: [    0     1     2 ... 65748 65749 65750] TEST: [65751 65752 65753 ... 82185 82186 82187]
TRAIN: [    0     1     2 ... 82185 82186 82187] TEST: [82188 82189 82190 ... 98622 98623 98624]
Out[55]:
Model Iteration Recall Fscore
count mean std mean std
0 xgb_V1 5 0.637 0.082 0.767 0.058
1 xgb_V2 5 0.660 0.073 0.785 0.050
2 xgb_V3 5 0.629 0.088 0.761 0.059
3 xgb_V4 5 0.660 0.073 0.782 0.050

7.2 Rolling-window Cross-validation on Downsampled Train Set¶

1. For selected candidate models from above step¶

2. Different downsample ratios¶

In [56]:
from sklearn.model_selection import TimeSeriesSplit

# separate minority and majority classes
negative = train[train.isFraud==0]
positive = train[train.isFraud==1]

time_split_cv_result = pd.DataFrame(columns = ['Downsample_Ratio', 'Model', 'Recall', 'Fscore'])

for i in [50,100,150,200]:
    # downsample majority
    neg_downsampled = resample(negative,
     replace=False, # sample without replacement to avoid overfittting                         
     n_samples=len(positive)*i, # match number in minority class
     random_state=27) # reproducible results
    
    # combine majority and upsampled minority
    downsampled = pd.concat([positive, neg_downsampled]).sort_values(by='step').reset_index(drop=True) #.drop(columns = ['step'])
    
    # check new class counts
    downsampled.isFraud.value_counts()

    X = downsampled.drop(['step','isFraud'], axis=1).fillna(0)
    y = downsampled[['isFraud']]

    print(len(y))
    print(np.sum(y.values))


    tscv = TimeSeriesSplit(n_splits=5)
    #TimeSeriesSplit(gap=0, max_train_size=None, n_splits=2, test_size=None)

    j = 0
    
    for train_index, test_index in tscv.split(X):
        j += 1
        
        print(i,j)
        
        #print("TRAIN:", train_index, "TEST:", test_index)
        X_train, X_test = X.iloc[train_index], X.iloc[test_index]
        y_train, y_test = y.iloc[train_index], y.iloc[test_index]
        
        xgb_pipeline_V1.fit(X_train, y_train)
        xgb_V1_recall = recall_score(y_test, xgb_pipeline_V1.predict(X_test))
        xgb_V1_fscore = f1_score(y_test, xgb_pipeline_V1.predict(X_test))
        
        #print(time_split_cv_result.tail(1))
        
        time_split_cv_result = pd.concat([time_split_cv_result, pd.DataFrame([{'Downsample_Ratio' : i,
                                                                               'Iteration' : j, 
                                                                                'Model' : 'xgb_V1', 
                                                                                'Recall' : xgb_V1_recall, 
                                                                                'Fscore' : xgb_V1_fscore}])])
        
        xgb_pipeline_V2.fit(X_train, y_train)
        xgb_V2_recall = recall_score(y_test, xgb_pipeline_V2.predict(X_test))
        xgb_V2_fscore = f1_score(y_test, xgb_pipeline_V2.predict(X_test))
        
        time_split_cv_result = pd.concat([time_split_cv_result, pd.DataFrame([{'Downsample_Ratio' : i,
                                                                               'Iteration' : j, 
                                                                                'Model' : 'xgb_V2', 
                                                                                'Recall' : xgb_V2_recall, 
                                                                                'Fscore' : xgb_V2_fscore}])])
                                                                               
        xgb_pipeline_V3.fit(X_train, y_train)
        xgb_V3_recall = recall_score(y_test, xgb_pipeline_V3.predict(X_test))
        xgb_V3_fscore = f1_score(y_test, xgb_pipeline_V3.predict(X_test))
        
        time_split_cv_result = pd.concat([time_split_cv_result, pd.DataFrame([{'Downsample_Ratio' : i,
                                                                               'Iteration' : j, 
                                                                                'Model' : 'xgb_V3', 
                                                                                'Recall' : xgb_V3_recall, 
                                                                                'Fscore' : xgb_V3_fscore}])])
                                                                               
        xgb_pipeline_V4.fit(X_train, y_train)
        xgb_V4_recall = recall_score(y_test, xgb_pipeline_V4.predict(X_test))
        xgb_V4_fscore = f1_score(y_test, xgb_pipeline_V4.predict(X_test))
        
        time_split_cv_result = pd.concat([time_split_cv_result, pd.DataFrame([{'Downsample_Ratio' : i,
                                                                               'Iteration' : j, 
                                                                                'Model' : 'xgb_V4', 
                                                                                'Recall' : xgb_V4_recall, 
                                                                                'Fscore' : xgb_V4_fscore}])])

time_split_cv_result.groupby(['Model','Downsample_Ratio'], as_index=False) \
                .agg({'Iteration':['count'], 'Recall':['mean','std'], 'Fscore':['mean','std']}) \
                .reset_index(drop=True)

8262
162
50 1
50 2
50 3
50 4
50 5
16362
162
100 1
100 2
100 3
100 4
100 5
24462
162
150 1
150 2
150 3
150 4
150 5
32562
162
200 1
200 2
200 3
200 4
200 5
Out[56]:
Model Downsample_Ratio Iteration Recall Fscore
count mean std mean std
0 xgb_V1 50 5 0.750 0.132 0.709 0.208
1 xgb_V1 100 5 0.741 0.135 0.705 0.239
2 xgb_V1 150 5 0.735 0.152 0.684 0.288
3 xgb_V1 200 5 0.676 0.167 0.790 0.129
4 xgb_V2 50 5 0.754 0.120 0.722 0.174
5 xgb_V2 100 5 0.722 0.101 0.717 0.233
6 xgb_V2 150 5 0.738 0.148 0.667 0.291
7 xgb_V2 200 5 0.668 0.165 0.784 0.126
8 xgb_V3 50 5 0.766 0.109 0.724 0.167
9 xgb_V3 100 5 0.728 0.115 0.708 0.209
10 xgb_V3 150 5 0.739 0.169 0.674 0.280
11 xgb_V3 200 5 0.660 0.173 0.774 0.138
12 xgb_V4 50 5 0.752 0.098 0.695 0.203
13 xgb_V4 100 5 0.731 0.143 0.731 0.196
14 xgb_V4 150 5 0.738 0.148 0.692 0.279
15 xgb_V4 200 5 0.672 0.174 0.767 0.110

7.2.1 Top models by Recall¶

In [57]:
grouped = time_split_cv_result.groupby(['Model','Downsample_Ratio'], as_index=False) \
                .agg({'Iteration':['count'], 'Recall':['mean','std'], 'Fscore':['mean','std']}) \
                .reset_index(drop=True)

grouped.columns = [f'{i}_{j}' if j != '' else f'{i}' for i,j in grouped.columns]

grouped.sort_values(by=['Recall_mean'], ascending=False).reset_index(drop=True)#.head(10)
Out[57]:
Model Downsample_Ratio Iteration_count Recall_mean Recall_std Fscore_mean Fscore_std
0 xgb_V3 50 5 0.766 0.109 0.724 0.167
1 xgb_V2 50 5 0.754 0.120 0.722 0.174
2 xgb_V4 50 5 0.752 0.098 0.695 0.203
3 xgb_V1 50 5 0.750 0.132 0.709 0.208
4 xgb_V1 100 5 0.741 0.135 0.705 0.239
5 xgb_V3 150 5 0.739 0.169 0.674 0.280
6 xgb_V2 150 5 0.738 0.148 0.667 0.291
7 xgb_V4 150 5 0.738 0.148 0.692 0.279
8 xgb_V1 150 5 0.735 0.152 0.684 0.288
9 xgb_V4 100 5 0.731 0.143 0.731 0.196
10 xgb_V3 100 5 0.728 0.115 0.708 0.209
11 xgb_V2 100 5 0.722 0.101 0.717 0.233
12 xgb_V1 200 5 0.676 0.167 0.790 0.129
13 xgb_V4 200 5 0.672 0.174 0.767 0.110
14 xgb_V2 200 5 0.668 0.165 0.784 0.126
15 xgb_V3 200 5 0.660 0.173 0.774 0.138
In [58]:
print(xgb_model_V3.get_xgb_params())

{'objective': 'binary:logistic', 'base_score': 0.5, 'booster': 'gbtree', 'colsample_bylevel': 1, 'colsample_bynode': 1, 'colsample_bytree': 1, 'eval_metric': None, 'gamma': 0, 'gpu_id': -1, 'grow_policy': 'depthwise', 'interaction_constraints': '', 'learning_rate': 0.3, 'max_bin': 256, 'max_cat_to_onehot': 4, 'max_delta_step': 0, 'max_depth': 15, 'max_leaves': 0, 'min_child_weight': 1, 'monotone_constraints': '()', 'n_jobs': -1, 'num_parallel_tree': 1, 'predictor': 'auto', 'random_state': 0, 'reg_alpha': 0, 'reg_lambda': 1, 'sampling_method': 'uniform', 'scale_pos_weight': 1, 'subsample': 0.9, 'tree_method': 'exact', 'validate_parameters': 1, 'verbosity': 0}

7.2.2 Top models by Fscore¶

In [59]:
grouped.sort_values(by='Fscore_mean', ascending=False).reset_index(drop=True).head(10)
Out[59]:
Model Downsample_Ratio Iteration_count Recall_mean Recall_std Fscore_mean Fscore_std
0 xgb_V1 200 5 0.676 0.167 0.790 0.129
1 xgb_V2 200 5 0.668 0.165 0.784 0.126
2 xgb_V3 200 5 0.660 0.173 0.774 0.138
3 xgb_V4 200 5 0.672 0.174 0.767 0.110
4 xgb_V4 100 5 0.731 0.143 0.731 0.196
5 xgb_V3 50 5 0.766 0.109 0.724 0.167
6 xgb_V2 50 5 0.754 0.120 0.722 0.174
7 xgb_V2 100 5 0.722 0.101 0.717 0.233
8 xgb_V1 50 5 0.750 0.132 0.709 0.208
9 xgb_V3 100 5 0.728 0.115 0.708 0.209
In [60]:
print(xgb_model_V2.get_xgb_params())

{'objective': 'binary:logistic', 'base_score': 0.5, 'booster': 'gbtree', 'colsample_bylevel': 1, 'colsample_bynode': 1, 'colsample_bytree': 1, 'eval_metric': None, 'gamma': 0, 'gpu_id': -1, 'grow_policy': 'depthwise', 'interaction_constraints': '', 'learning_rate': 0.3, 'max_bin': 256, 'max_cat_to_onehot': 4, 'max_delta_step': 0, 'max_depth': 15, 'max_leaves': 0, 'min_child_weight': 1, 'monotone_constraints': '()', 'n_jobs': -1, 'num_parallel_tree': 1, 'predictor': 'auto', 'random_state': 0, 'reg_alpha': 0, 'reg_lambda': 1, 'sampling_method': 'uniform', 'scale_pos_weight': 1, 'subsample': 0.85, 'tree_method': 'exact', 'validate_parameters': 1, 'verbosity': 0}

7.3 Training the selected model on complete Train Set¶

In [99]:
# separate minority and majority classes
negative = train[train.isFraud==0]
positive = train[train.isFraud==1]

# downsample majority
neg_downsampled = resample(negative,
 replace=False, # sample without replacement to avoid overfittting                    
 n_samples=len(positive)*50, # match number in minority class
 random_state=27) # reproducible results

# combine majority and upsampled minority
downsampled = pd.concat([positive, neg_downsampled]).sort_values(by='step').reset_index(drop=True)

# check new class counts
downsampled.isFraud.value_counts()

xgb_model = xgboost.XGBClassifier(subsample=0.9, max_depth=15, learning_rate=0.3, objective= 'binary:logistic',n_jobs=-1,verbosity = 0)
xgb_pipeline = Pipeline(steps=[('preprocess', full_processor), ('feature_selection', SelectFromModel(xgboost.XGBClassifier())), ('model', xgb_model)])
In [100]:
x_train = downsampled.drop(['step','isFraud'], axis=1).fillna(0)
y_train = downsampled[['isFraud']]
In [101]:
xgb_pipeline.fit(x_train, y_train)
Out[101]:
Pipeline(steps=[('preprocess',
                 ColumnTransformer(transformers=[('number',
                                                  Pipeline(steps=[('impute',
                                                                   SimpleImputer())]),
                                                  Index(['amount', 'oldbalanceOrg', 'newbalanceOrig', 'oldbalanceDest', 'newbalanceDest', 'nameOrig_rolling_txn_count_1day', 'nameOrig_rolling_txn_count_3day', 'nameOrig_rolling_txn_count_7day', 'nameOrig_rolling_txn_count_10day', 'nameOrig_rol...
                               gamma=0, gpu_id=-1, grow_policy='depthwise',
                               importance_type=None, interaction_constraints='',
                               learning_rate=0.3, max_bin=256,
                               max_cat_to_onehot=4, max_delta_step=0,
                               max_depth=15, max_leaves=0, min_child_weight=1,
                               missing=nan, monotone_constraints='()',
                               n_estimators=100, n_jobs=-1, num_parallel_tree=1,
                               predictor='auto', random_state=0, reg_alpha=0,
                               reg_lambda=1, ...))])
In [102]:
x_test = test.drop(['step','isFraud'], axis=1).fillna(0)
y_test = test[['isFraud']]
In [103]:
x_test
Out[103]:
type amount oldbalanceOrg newbalanceOrig oldbalanceDest newbalanceDest nameOrig_rolling_txn_count_1day nameOrig_rolling_txn_count_3day nameOrig_rolling_txn_count_7day nameOrig_rolling_txn_count_10day nameOrig_rolling_txn_count_14day nameOrig_rolling_txn_sum_1day nameOrig_rolling_txn_sum_3day nameOrig_rolling_txn_sum_7day nameOrig_rolling_txn_sum_10day nameOrig_rolling_txn_sum_14day nameOrig_rolling_txn_count_mean_7day nameOrig_rolling_txn_count_mean_10day nameOrig_rolling_txn_count_mean_14day nameOrig_rolling_txn_amount_mean_7day nameOrig_rolling_txn_amount_mean_10day nameOrig_rolling_txn_amount_mean_14day nameOrig_rolling_txn_amount_max_7day nameOrig_rolling_txn_amount_max_10day nameOrig_rolling_txn_amount_max_14day nameDest_rolling_txn_count_1day nameDest_rolling_txn_count_3day nameDest_rolling_txn_count_7day nameDest_rolling_txn_count_10day nameDest_rolling_txn_count_14day nameDest_rolling_txn_sum_1day nameDest_rolling_txn_sum_3day nameDest_rolling_txn_sum_7day nameDest_rolling_txn_sum_10day nameDest_rolling_txn_sum_14day nameDest_rolling_txn_count_mean_7day nameDest_rolling_txn_count_mean_10day nameDest_rolling_txn_count_mean_14day nameDest_rolling_txn_amount_mean_7day nameDest_rolling_txn_amount_mean_10day nameDest_rolling_txn_amount_mean_14day nameDest_rolling_txn_amount_max_7day nameDest_rolling_txn_amount_max_10day nameDest_rolling_txn_amount_max_14day nameOrig_nameDest_rolling_txn_count_1day nameOrig_nameDest_rolling_txn_count_3day nameOrig_nameDest_rolling_txn_count_7day nameOrig_nameDest_rolling_txn_count_10day nameOrig_nameDest_rolling_txn_count_14day nameOrig_nameDest_rolling_txn_sum_1day nameOrig_nameDest_rolling_txn_sum_3day nameOrig_nameDest_rolling_txn_sum_7day nameOrig_nameDest_rolling_txn_sum_10day nameOrig_nameDest_rolling_txn_sum_14day nameOrig_nameDest_rolling_txn_count_mean_7day nameOrig_nameDest_rolling_txn_count_mean_10day nameOrig_nameDest_rolling_txn_count_mean_14day nameOrig_nameDest_rolling_txn_amount_mean_7day nameOrig_nameDest_rolling_txn_amount_mean_10day nameOrig_nameDest_rolling_txn_amount_mean_14day nameOrig_nameDest_rolling_txn_amount_max_7day nameOrig_nameDest_rolling_txn_amount_max_10day nameOrig_nameDest_rolling_txn_amount_max_14day nameOrig_type_rolling_txn_count_1day nameOrig_type_rolling_txn_count_3day nameOrig_type_rolling_txn_count_7day nameOrig_type_rolling_txn_count_10day nameOrig_type_rolling_txn_count_14day nameOrig_type_rolling_txn_sum_1day nameOrig_type_rolling_txn_sum_3day nameOrig_type_rolling_txn_sum_7day nameOrig_type_rolling_txn_sum_10day nameOrig_type_rolling_txn_sum_14day nameOrig_type_rolling_txn_count_mean_7day nameOrig_type_rolling_txn_count_mean_10day nameOrig_type_rolling_txn_count_mean_14day nameOrig_type_rolling_txn_amount_mean_7day nameOrig_type_rolling_txn_amount_mean_10day nameOrig_type_rolling_txn_amount_mean_14day nameOrig_type_rolling_txn_amount_max_7day nameOrig_type_rolling_txn_amount_max_10day nameOrig_type_rolling_txn_amount_max_14day nameDest_type_rolling_txn_count_1day nameDest_type_rolling_txn_count_3day nameDest_type_rolling_txn_count_7day nameDest_type_rolling_txn_count_10day nameDest_type_rolling_txn_count_14day nameDest_type_rolling_txn_sum_1day nameDest_type_rolling_txn_sum_3day nameDest_type_rolling_txn_sum_7day nameDest_type_rolling_txn_sum_10day nameDest_type_rolling_txn_sum_14day nameDest_type_rolling_txn_count_mean_7day nameDest_type_rolling_txn_count_mean_10day nameDest_type_rolling_txn_count_mean_14day nameDest_type_rolling_txn_amount_mean_7day nameDest_type_rolling_txn_amount_mean_10day nameDest_type_rolling_txn_amount_mean_14day nameDest_type_rolling_txn_amount_max_7day nameDest_type_rolling_txn_amount_max_10day nameDest_type_rolling_txn_amount_max_14day nameOrig_nameDest_type_rolling_txn_count_1day nameOrig_nameDest_type_rolling_txn_count_3day nameOrig_nameDest_type_rolling_txn_count_7day nameOrig_nameDest_type_rolling_txn_count_10day nameOrig_nameDest_type_rolling_txn_count_14day nameOrig_nameDest_type_rolling_txn_sum_1day nameOrig_nameDest_type_rolling_txn_sum_3day nameOrig_nameDest_type_rolling_txn_sum_7day nameOrig_nameDest_type_rolling_txn_sum_10day nameOrig_nameDest_type_rolling_txn_sum_14day nameOrig_nameDest_type_rolling_txn_count_mean_7day nameOrig_nameDest_type_rolling_txn_count_mean_10day nameOrig_nameDest_type_rolling_txn_count_mean_14day nameOrig_nameDest_type_rolling_txn_amount_mean_7day nameOrig_nameDest_type_rolling_txn_amount_mean_10day nameOrig_nameDest_type_rolling_txn_amount_mean_14day nameOrig_nameDest_type_rolling_txn_amount_max_7day nameOrig_nameDest_type_rolling_txn_amount_max_10day nameOrig_nameDest_type_rolling_txn_amount_max_14day nameOrig_time_since_last_txn nameDest_time_since_last_txn nameOrig_nameDest_time_since_last_txn nameOrig_type_time_since_last_txn nameDest_type_time_since_last_txn nameOrig_nameDest_type_time_since_last_txn nameOrig_txnCount_velocity_ratio_over_7day nameOrig_txnCount_velocity_ratio_over_10day nameOrig_txnCount_velocity_ratio_over_14day nameOrig_amount_velocity_ratio_over_7day nameOrig_amount_velocity_ratio_over_10day nameOrig_amount_velocity_ratio_over_14day nameOrig_amount_max_velocity_ratio_over_7day nameOrig_amount_max_velocity_ratio_over_10day nameOrig_amount_max_velocity_ratio_over_14day nameDest_txnCount_velocity_ratio_over_7day nameDest_txnCount_velocity_ratio_over_10day nameDest_txnCount_velocity_ratio_over_14day nameDest_amount_velocity_ratio_over_7day nameDest_amount_velocity_ratio_over_10day nameDest_amount_velocity_ratio_over_14day nameDest_amount_max_velocity_ratio_over_7day nameDest_amount_max_velocity_ratio_over_10day nameDest_amount_max_velocity_ratio_over_14day nameOrig_nameDest_txnCount_velocity_ratio_over_7day nameOrig_nameDest_txnCount_velocity_ratio_over_10day nameOrig_nameDest_txnCount_velocity_ratio_over_14day nameOrig_nameDest_amount_velocity_ratio_over_7day nameOrig_nameDest_amount_velocity_ratio_over_10day nameOrig_nameDest_amount_velocity_ratio_over_14day nameOrig_nameDest_amount_max_velocity_ratio_over_7day nameOrig_nameDest_amount_max_velocity_ratio_over_10day nameOrig_nameDest_amount_max_velocity_ratio_over_14day nameOrig_type_txnCount_velocity_ratio_over_7day nameOrig_type_txnCount_velocity_ratio_over_10day nameOrig_type_txnCount_velocity_ratio_over_14day nameOrig_type_amount_velocity_ratio_over_7day nameOrig_type_amount_velocity_ratio_over_10day nameOrig_type_amount_velocity_ratio_over_14day nameOrig_type_amount_max_velocity_ratio_over_7day nameOrig_type_amount_max_velocity_ratio_over_10day nameOrig_type_amount_max_velocity_ratio_over_14day nameDest_type_txnCount_velocity_ratio_over_7day nameDest_type_txnCount_velocity_ratio_over_10day nameDest_type_txnCount_velocity_ratio_over_14day nameDest_type_amount_velocity_ratio_over_7day nameDest_type_amount_velocity_ratio_over_10day nameDest_type_amount_velocity_ratio_over_14day nameDest_type_amount_max_velocity_ratio_over_7day nameDest_type_amount_max_velocity_ratio_over_10day nameDest_type_amount_max_velocity_ratio_over_14day nameOrig_nameDest_type_txnCount_velocity_ratio_over_7day nameOrig_nameDest_type_txnCount_velocity_ratio_over_10day nameOrig_nameDest_type_txnCount_velocity_ratio_over_14day nameOrig_nameDest_type_amount_velocity_ratio_over_7day nameOrig_nameDest_type_amount_velocity_ratio_over_10day nameOrig_nameDest_type_amount_velocity_ratio_over_14day nameOrig_nameDest_type_amount_max_velocity_ratio_over_7day nameOrig_nameDest_type_amount_max_velocity_ratio_over_10day nameOrig_nameDest_type_amount_max_velocity_ratio_over_14day nameOrig_had_prev_fraud nameDest_had_prev_fraud nameOrig_nameDest_had_prev_fraud nameOrig_type_had_prev_fraud nameDest_type_had_prev_fraud nameOrig_nameDest_type_had_prev_fraud changeBalanceOrg_prcnt changeBalanceDest_prcnt
17 TRANSFER 67277.540 204160.000 136882.460 457734.560 525012.100 1.000 1.000 1.000 1.000 1.000 67277.540 67277.540 67277.540 67277.540 67277.540 0.006 0.004 0.003 400.462 280.323 200.231 67277.540 67277.540 67277.540 1.000 2.000 2.000 2.000 2.000 67277.540 130533.950 130533.950 130533.950 130533.950 0.012 0.008 0.006 776.988 543.891 388.494 67277.540 67277.540 67277.540 1.000 1.000 1.000 1.000 1.000 67277.540 67277.540 67277.540 67277.540 67277.540 0.006 0.004 0.003 400.462 280.323 200.231 67277.540 67277.540 67277.540 1.000 1.000 1.000 1.000 1.000 67277.540 67277.540 67277.540 67277.540 67277.540 0.006 0.004 0.003 400.462 280.323 200.231 67277.540 67277.540 67277.540 1.000 1.000 1.000 1.000 1.000 67277.540 67277.540 67277.540 67277.540 67277.540 0.006 0.004 0.003 400.462 280.323 200.231 67277.540 67277.540 67277.540 1.000 1.000 1.000 1.000 1.000 67277.540 67277.540 67277.540 67277.540 67277.540 0.006 0.004 0.003 400.462 280.323 200.231 67277.540 67277.540 67277.540 0.000 45.000 0.000 0.000 393.000 0.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 84.000 120.000 168.000 86.588 123.697 173.175 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 0.000 0.000 0.000 0.000 0.000 0.000 -32.953 14.698
150 CASH_OUT 16508.840 0.000 0.000 938660.930 955169.770 1.000 1.000 1.000 1.000 1.000 16508.840 16508.840 16508.840 16508.840 16508.840 0.006 0.004 0.003 98.267 68.787 49.133 16508.840 16508.840 16508.840 1.000 1.000 1.000 1.000 1.000 16508.840 16508.840 16508.840 16508.840 16508.840 0.006 0.004 0.003 98.267 68.787 49.133 16508.840 16508.840 16508.840 1.000 1.000 1.000 1.000 1.000 16508.840 16508.840 16508.840 16508.840 16508.840 0.006 0.004 0.003 98.267 68.787 49.133 16508.840 16508.840 16508.840 1.000 1.000 1.000 1.000 1.000 16508.840 16508.840 16508.840 16508.840 16508.840 0.006 0.004 0.003 98.267 68.787 49.133 16508.840 16508.840 16508.840 1.000 1.000 1.000 1.000 1.000 16508.840 16508.840 16508.840 16508.840 16508.840 0.006 0.004 0.003 98.267 68.787 49.133 16508.840 16508.840 16508.840 1.000 1.000 1.000 1.000 1.000 16508.840 16508.840 16508.840 16508.840 16508.840 0.006 0.004 0.003 98.267 68.787 49.133 16508.840 16508.840 16508.840 0.000 364.000 0.000 0.000 456.000 0.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 1.759
169 TRANSFER 493790.130 0.000 0.000 623627.870 1117418.000 1.000 1.000 1.000 1.000 1.000 493790.130 493790.130 493790.130 493790.130 493790.130 0.006 0.004 0.003 2939.227 2057.459 1469.613 493790.130 493790.130 493790.130 1.000 1.000 1.000 1.000 4.000 493790.130 493790.130 493790.130 493790.130 1171692.630 0.006 0.004 0.012 2939.227 2057.459 3487.180 493790.130 493790.130 493790.130 1.000 1.000 1.000 1.000 1.000 493790.130 493790.130 493790.130 493790.130 493790.130 0.006 0.004 0.003 2939.227 2057.459 1469.613 493790.130 493790.130 493790.130 1.000 1.000 1.000 1.000 1.000 493790.130 493790.130 493790.130 493790.130 493790.130 0.006 0.004 0.003 2939.227 2057.459 1469.613 493790.130 493790.130 493790.130 1.000 1.000 1.000 1.000 2.000 493790.130 493790.130 493790.130 493790.130 706914.820 0.006 0.004 0.006 2939.227 2057.459 2103.913 493790.130 493790.130 493790.130 1.000 1.000 1.000 1.000 1.000 493790.130 493790.130 493790.130 493790.130 493790.130 0.006 0.004 0.003 2939.227 2057.459 1469.613 493790.130 493790.130 493790.130 0.000 290.000 0.000 0.000 309.000 0.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 84.000 168.000 240.000 141.602 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 168.000 168.000 240.000 234.701 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 79.180
235 CASH_OUT 382268.420 0.000 0.000 13323843.460 13706111.880 1.000 1.000 1.000 1.000 1.000 382268.420 382268.420 382268.420 382268.420 382268.420 0.006 0.004 0.003 2275.407 1592.785 1137.704 382268.420 382268.420 382268.420 1.000 1.000 1.000 1.000 5.000 382268.420 382268.420 382268.420 382268.420 7591876.780 0.006 0.004 0.015 2275.407 1592.785 22594.871 382268.420 382268.420 4048890.050 1.000 1.000 1.000 1.000 1.000 382268.420 382268.420 382268.420 382268.420 382268.420 0.006 0.004 0.003 2275.407 1592.785 1137.704 382268.420 382268.420 382268.420 1.000 1.000 1.000 1.000 1.000 382268.420 382268.420 382268.420 382268.420 382268.420 0.006 0.004 0.003 2275.407 1592.785 1137.704 382268.420 382268.420 382268.420 1.000 1.000 1.000 1.000 2.000 382268.420 382268.420 382268.420 382268.420 653703.110 0.006 0.004 0.006 2275.407 1592.785 1945.545 382268.420 382268.420 382268.420 1.000 1.000 1.000 1.000 1.000 382268.420 382268.420 382268.420 382268.420 382268.420 0.006 0.004 0.003 2275.407 1592.785 1137.704 382268.420 382268.420 382268.420 0.000 241.000 0.000 0.000 241.000 0.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 67.200 168.000 240.000 16.918 1.000 1.000 0.094 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 168.000 168.000 240.000 196.484 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 2.869
254 DEBIT 2737.510 2720.000 0.000 32886.520 35624.030 1.000 1.000 1.000 1.000 1.000 2737.510 2737.510 2737.510 2737.510 2737.510 0.006 0.004 0.003 16.295 11.406 8.147 2737.510 2737.510 2737.510 1.000 1.000 1.000 1.000 2.000 2737.510 2737.510 2737.510 2737.510 35624.030 0.006 0.004 0.006 16.295 11.406 106.024 2737.510 2737.510 32886.520 1.000 1.000 1.000 1.000 1.000 2737.510 2737.510 2737.510 2737.510 2737.510 0.006 0.004 0.003 16.295 11.406 8.147 2737.510 2737.510 2737.510 1.000 1.000 1.000 1.000 1.000 2737.510 2737.510 2737.510 2737.510 2737.510 0.006 0.004 0.003 16.295 11.406 8.147 2737.510 2737.510 2737.510 1.000 1.000 1.000 1.000 1.000 2737.510 2737.510 2737.510 2737.510 2737.510 0.006 0.004 0.003 16.295 11.406 8.147 2737.510 2737.510 2737.510 1.000 1.000 1.000 1.000 1.000 2737.510 2737.510 2737.510 2737.510 2737.510 0.006 0.004 0.003 16.295 11.406 8.147 2737.510 2737.510 2737.510 0.000 318.000 0.000 0.000 0.000 0.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 168.000 168.000 240.000 25.820 1.000 1.000 0.083 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 0.000 0.000 0.000 0.000 0.000 0.000 -99.963 8.324
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
99701 CASH_IN 40488.480 8288163.010 8328651.490 1138997.060 1098508.580 1.000 1.000 1.000 1.000 1.000 40488.480 40488.480 40488.480 40488.480 40488.480 0.006 0.004 0.003 241.003 168.702 120.501 40488.480 40488.480 40488.480 1.000 1.000 2.000 2.000 6.000 40488.480 40488.480 150200.650 150200.650 1561771.430 0.012 0.008 0.018 894.051 625.836 4648.129 109712.170 109712.170 760281.560 1.000 1.000 1.000 1.000 1.000 40488.480 40488.480 40488.480 40488.480 40488.480 0.006 0.004 0.003 241.003 168.702 120.501 40488.480 40488.480 40488.480 1.000 1.000 1.000 1.000 1.000 40488.480 40488.480 40488.480 40488.480 40488.480 0.006 0.004 0.003 241.003 168.702 120.501 40488.480 40488.480 40488.480 1.000 1.000 2.000 2.000 3.000 40488.480 40488.480 150200.650 150200.650 549852.060 0.012 0.008 0.009 894.051 625.836 1636.464 109712.170 109712.170 399651.410 1.000 1.000 1.000 1.000 1.000 40488.480 40488.480 40488.480 40488.480 40488.480 0.006 0.004 0.003 241.003 168.702 120.501 40488.480 40488.480 40488.480 0.000 96.000 0.000 0.000 96.000 0.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 84.000 120.000 56.000 45.287 64.695 8.711 0.369 0.369 0.053 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 84.000 120.000 112.000 45.287 64.695 24.741 0.369 0.369 0.101 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 0.000 0.000 0.000 0.000 0.000 0.000 0.489 -3.555
99741 CASH_OUT 304772.540 0.000 0.000 310756.710 615529.260 1.000 1.000 1.000 1.000 1.000 304772.540 304772.540 304772.540 304772.540 304772.540 0.006 0.004 0.003 1814.122 1269.886 907.061 304772.540 304772.540 304772.540 1.000 1.000 1.000 1.000 2.000 304772.540 304772.540 304772.540 304772.540 398677.060 0.006 0.004 0.006 1814.122 1269.886 1186.539 304772.540 304772.540 304772.540 1.000 1.000 1.000 1.000 1.000 304772.540 304772.540 304772.540 304772.540 304772.540 0.006 0.004 0.003 1814.122 1269.886 907.061 304772.540 304772.540 304772.540 1.000 1.000 1.000 1.000 1.000 304772.540 304772.540 304772.540 304772.540 304772.540 0.006 0.004 0.003 1814.122 1269.886 907.061 304772.540 304772.540 304772.540 1.000 1.000 1.000 1.000 2.000 304772.540 304772.540 304772.540 304772.540 398677.060 0.006 0.004 0.006 1814.122 1269.886 1186.539 304772.540 304772.540 304772.540 1.000 1.000 1.000 1.000 1.000 304772.540 304772.540 304772.540 304772.540 304772.540 0.006 0.004 0.003 1814.122 1269.886 907.061 304772.540 304772.540 304772.540 0.000 325.000 0.000 0.000 325.000 0.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 168.000 168.000 240.000 256.858 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 168.000 168.000 240.000 256.858 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 98.074
99773 CASH_OUT 425236.800 272416.110 0.000 1829866.800 2255103.600 1.000 1.000 1.000 1.000 1.000 425236.800 425236.800 425236.800 425236.800 425236.800 0.006 0.004 0.003 2531.171 1771.820 1265.586 425236.800 425236.800 425236.800 1.000 1.000 1.000 1.000 2.000 425236.800 425236.800 425236.800 425236.800 507630.230 0.006 0.004 0.006 2531.171 1771.820 1510.804 425236.800 425236.800 425236.800 1.000 1.000 1.000 1.000 1.000 425236.800 425236.800 425236.800 425236.800 425236.800 0.006 0.004 0.003 2531.171 1771.820 1265.586 425236.800 425236.800 425236.800 1.000 1.000 1.000 1.000 1.000 425236.800 425236.800 425236.800 425236.800 425236.800 0.006 0.004 0.003 2531.171 1771.820 1265.586 425236.800 425236.800 425236.800 1.000 1.000 1.000 1.000 2.000 425236.800 425236.800 425236.800 425236.800 507630.230 0.006 0.004 0.006 2531.171 1771.820 1510.804 425236.800 425236.800 425236.800 1.000 1.000 1.000 1.000 1.000 425236.800 425236.800 425236.800 425236.800 425236.800 0.006 0.004 0.003 2531.171 1771.820 1265.586 425236.800 425236.800 425236.800 0.000 285.000 0.000 0.000 285.000 0.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 168.000 168.000 240.000 281.464 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 168.000 168.000 240.000 281.464 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 0.000 0.000 0.000 0.000 0.000 0.000 -100.000 23.239
99857 CASH_IN 128654.360 83214.000 211868.360 9367051.890 9238397.530 1.000 1.000 1.000 1.000 1.000 128654.360 128654.360 128654.360 128654.360 128654.360 0.006 0.004 0.003 765.800 536.060 382.900 128654.360 128654.360 128654.360 2.000 2.000 2.000 2.000 5.000 1128618.730 1128618.730 1128618.730 1128618.730 3761151.610 0.012 0.008 0.015 6717.969 4702.578 11193.904 999964.370 999964.370 1872784.870 1.000 1.000 1.000 1.000 1.000 128654.360 128654.360 128654.360 128654.360 128654.360 0.006 0.004 0.003 765.800 536.060 382.900 128654.360 128654.360 128654.360 1.000 1.000 1.000 1.000 1.000 128654.360 128654.360 128654.360 128654.360 128654.360 0.006 0.004 0.003 765.800 536.060 382.900 128654.360 128654.360 128654.360 1.000 1.000 1.000 1.000 1.000 128654.360 128654.360 128654.360 128654.360 128654.360 0.006 0.004 0.003 765.800 536.060 382.900 128654.360 128654.360 128654.360 1.000 1.000 1.000 1.000 1.000 128654.360 128654.360 128654.360 128654.360 128654.360 0.006 0.004 0.003 765.800 536.060 382.900 128654.360 128654.360 128654.360 0.000 22.000 0.000 0.000 359.000 0.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 134.400 168.000 240.000 100.824 1.129 1.129 0.603 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 0.000 0.000 0.000 0.000 0.000 0.000 154.605 -1.373
99981 CASH_OUT 799123.570 799123.570 0.000 5474293.010 6273416.580 1.000 1.000 1.000 1.000 1.000 799123.570 799123.570 799123.570 799123.570 799123.570 0.006 0.004 0.003 4756.688 3329.682 2378.344 799123.570 799123.570 799123.570 1.000 1.000 1.000 1.000 3.000 799123.570 799123.570 799123.570 799123.570 1004983.340 0.006 0.004 0.009 4756.688 3329.682 2991.022 799123.570 799123.570 799123.570 1.000 1.000 1.000 1.000 1.000 799123.570 799123.570 799123.570 799123.570 799123.570 0.006 0.004 0.003 4756.688 3329.682 2378.344 799123.570 799123.570 799123.570 1.000 1.000 1.000 1.000 1.000 799123.570 799123.570 799123.570 799123.570 799123.570 0.006 0.004 0.003 4756.688 3329.682 2378.344 799123.570 799123.570 799123.570 1.000 1.000 1.000 1.000 3.000 799123.570 799123.570 799123.570 799123.570 1004983.340 0.006 0.004 0.009 4756.688 3329.682 2991.022 799123.570 799123.570 799123.570 1.000 1.000 1.000 1.000 1.000 799123.570 799123.570 799123.570 799123.570 799123.570 0.006 0.004 0.003 4756.688 3329.682 2378.344 799123.570 799123.570 799123.570 0.000 302.000 0.000 0.000 302.000 0.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 112.000 168.000 240.000 267.174 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 112.000 168.000 240.000 267.174 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 0.000 0.000 0.000 0.000 0.000 0.000 -100.000 14.598

1375 rows × 188 columns

In [104]:
np.sum(xgb_pipeline.predict(x_test))
Out[104]:
32

8. Generalization Performance¶

In [145]:
print('XGBoost Test Recall', round(recall_score(y_test, xgb_pipeline.predict(x_test)),3))
print('XGBoost Test F-Score', round(f1_score(y_test, xgb_pipeline.predict(x_test)),3))

XGBoost Test Recall 0.882
XGBoost Test F-Score 0.909
In [106]:
xgb_pipeline.named_steps['feature_selection'].get_feature_names_out()
Out[106]:
array(['x0', 'x1', 'x3', 'x4', 'x15', 'x18', 'x19', 'x25', 'x26', 'x27',
       'x29', 'x31', 'x34', 'x38', 'x40', 'x41', 'x42', 'x82', 'x83',
       'x87', 'x90', 'x98', 'x136', 'x138', 'x140', 'x165', 'x167',
       'x183', 'x185', 'x186', 'x188', 'x190'], dtype=object)
In [107]:
final_features = list(pd.Series(xgb_pipeline.named_steps['feature_selection'].get_feature_names_out()).str.replace('x',''))

final_features = [int(i) for i in final_features]
In [108]:
x_test.head()
Out[108]:
type amount oldbalanceOrg newbalanceOrig oldbalanceDest newbalanceDest nameOrig_rolling_txn_count_1day nameOrig_rolling_txn_count_3day nameOrig_rolling_txn_count_7day nameOrig_rolling_txn_count_10day nameOrig_rolling_txn_count_14day nameOrig_rolling_txn_sum_1day nameOrig_rolling_txn_sum_3day nameOrig_rolling_txn_sum_7day nameOrig_rolling_txn_sum_10day nameOrig_rolling_txn_sum_14day nameOrig_rolling_txn_count_mean_7day nameOrig_rolling_txn_count_mean_10day nameOrig_rolling_txn_count_mean_14day nameOrig_rolling_txn_amount_mean_7day nameOrig_rolling_txn_amount_mean_10day nameOrig_rolling_txn_amount_mean_14day nameOrig_rolling_txn_amount_max_7day nameOrig_rolling_txn_amount_max_10day nameOrig_rolling_txn_amount_max_14day nameDest_rolling_txn_count_1day nameDest_rolling_txn_count_3day nameDest_rolling_txn_count_7day nameDest_rolling_txn_count_10day nameDest_rolling_txn_count_14day nameDest_rolling_txn_sum_1day nameDest_rolling_txn_sum_3day nameDest_rolling_txn_sum_7day nameDest_rolling_txn_sum_10day nameDest_rolling_txn_sum_14day nameDest_rolling_txn_count_mean_7day nameDest_rolling_txn_count_mean_10day nameDest_rolling_txn_count_mean_14day nameDest_rolling_txn_amount_mean_7day nameDest_rolling_txn_amount_mean_10day nameDest_rolling_txn_amount_mean_14day nameDest_rolling_txn_amount_max_7day nameDest_rolling_txn_amount_max_10day nameDest_rolling_txn_amount_max_14day nameOrig_nameDest_rolling_txn_count_1day nameOrig_nameDest_rolling_txn_count_3day nameOrig_nameDest_rolling_txn_count_7day nameOrig_nameDest_rolling_txn_count_10day nameOrig_nameDest_rolling_txn_count_14day nameOrig_nameDest_rolling_txn_sum_1day nameOrig_nameDest_rolling_txn_sum_3day nameOrig_nameDest_rolling_txn_sum_7day nameOrig_nameDest_rolling_txn_sum_10day nameOrig_nameDest_rolling_txn_sum_14day nameOrig_nameDest_rolling_txn_count_mean_7day nameOrig_nameDest_rolling_txn_count_mean_10day nameOrig_nameDest_rolling_txn_count_mean_14day nameOrig_nameDest_rolling_txn_amount_mean_7day nameOrig_nameDest_rolling_txn_amount_mean_10day nameOrig_nameDest_rolling_txn_amount_mean_14day nameOrig_nameDest_rolling_txn_amount_max_7day nameOrig_nameDest_rolling_txn_amount_max_10day nameOrig_nameDest_rolling_txn_amount_max_14day nameOrig_type_rolling_txn_count_1day nameOrig_type_rolling_txn_count_3day nameOrig_type_rolling_txn_count_7day nameOrig_type_rolling_txn_count_10day nameOrig_type_rolling_txn_count_14day nameOrig_type_rolling_txn_sum_1day nameOrig_type_rolling_txn_sum_3day nameOrig_type_rolling_txn_sum_7day nameOrig_type_rolling_txn_sum_10day nameOrig_type_rolling_txn_sum_14day nameOrig_type_rolling_txn_count_mean_7day nameOrig_type_rolling_txn_count_mean_10day nameOrig_type_rolling_txn_count_mean_14day nameOrig_type_rolling_txn_amount_mean_7day nameOrig_type_rolling_txn_amount_mean_10day nameOrig_type_rolling_txn_amount_mean_14day nameOrig_type_rolling_txn_amount_max_7day nameOrig_type_rolling_txn_amount_max_10day nameOrig_type_rolling_txn_amount_max_14day nameDest_type_rolling_txn_count_1day nameDest_type_rolling_txn_count_3day nameDest_type_rolling_txn_count_7day nameDest_type_rolling_txn_count_10day nameDest_type_rolling_txn_count_14day nameDest_type_rolling_txn_sum_1day nameDest_type_rolling_txn_sum_3day nameDest_type_rolling_txn_sum_7day nameDest_type_rolling_txn_sum_10day nameDest_type_rolling_txn_sum_14day nameDest_type_rolling_txn_count_mean_7day nameDest_type_rolling_txn_count_mean_10day nameDest_type_rolling_txn_count_mean_14day nameDest_type_rolling_txn_amount_mean_7day nameDest_type_rolling_txn_amount_mean_10day nameDest_type_rolling_txn_amount_mean_14day nameDest_type_rolling_txn_amount_max_7day nameDest_type_rolling_txn_amount_max_10day nameDest_type_rolling_txn_amount_max_14day nameOrig_nameDest_type_rolling_txn_count_1day nameOrig_nameDest_type_rolling_txn_count_3day nameOrig_nameDest_type_rolling_txn_count_7day nameOrig_nameDest_type_rolling_txn_count_10day nameOrig_nameDest_type_rolling_txn_count_14day nameOrig_nameDest_type_rolling_txn_sum_1day nameOrig_nameDest_type_rolling_txn_sum_3day nameOrig_nameDest_type_rolling_txn_sum_7day nameOrig_nameDest_type_rolling_txn_sum_10day nameOrig_nameDest_type_rolling_txn_sum_14day nameOrig_nameDest_type_rolling_txn_count_mean_7day nameOrig_nameDest_type_rolling_txn_count_mean_10day nameOrig_nameDest_type_rolling_txn_count_mean_14day nameOrig_nameDest_type_rolling_txn_amount_mean_7day nameOrig_nameDest_type_rolling_txn_amount_mean_10day nameOrig_nameDest_type_rolling_txn_amount_mean_14day nameOrig_nameDest_type_rolling_txn_amount_max_7day nameOrig_nameDest_type_rolling_txn_amount_max_10day nameOrig_nameDest_type_rolling_txn_amount_max_14day nameOrig_time_since_last_txn nameDest_time_since_last_txn nameOrig_nameDest_time_since_last_txn nameOrig_type_time_since_last_txn nameDest_type_time_since_last_txn nameOrig_nameDest_type_time_since_last_txn nameOrig_txnCount_velocity_ratio_over_7day nameOrig_txnCount_velocity_ratio_over_10day nameOrig_txnCount_velocity_ratio_over_14day nameOrig_amount_velocity_ratio_over_7day nameOrig_amount_velocity_ratio_over_10day nameOrig_amount_velocity_ratio_over_14day nameOrig_amount_max_velocity_ratio_over_7day nameOrig_amount_max_velocity_ratio_over_10day nameOrig_amount_max_velocity_ratio_over_14day nameDest_txnCount_velocity_ratio_over_7day nameDest_txnCount_velocity_ratio_over_10day nameDest_txnCount_velocity_ratio_over_14day nameDest_amount_velocity_ratio_over_7day nameDest_amount_velocity_ratio_over_10day nameDest_amount_velocity_ratio_over_14day nameDest_amount_max_velocity_ratio_over_7day nameDest_amount_max_velocity_ratio_over_10day nameDest_amount_max_velocity_ratio_over_14day nameOrig_nameDest_txnCount_velocity_ratio_over_7day nameOrig_nameDest_txnCount_velocity_ratio_over_10day nameOrig_nameDest_txnCount_velocity_ratio_over_14day nameOrig_nameDest_amount_velocity_ratio_over_7day nameOrig_nameDest_amount_velocity_ratio_over_10day nameOrig_nameDest_amount_velocity_ratio_over_14day nameOrig_nameDest_amount_max_velocity_ratio_over_7day nameOrig_nameDest_amount_max_velocity_ratio_over_10day nameOrig_nameDest_amount_max_velocity_ratio_over_14day nameOrig_type_txnCount_velocity_ratio_over_7day nameOrig_type_txnCount_velocity_ratio_over_10day nameOrig_type_txnCount_velocity_ratio_over_14day nameOrig_type_amount_velocity_ratio_over_7day nameOrig_type_amount_velocity_ratio_over_10day nameOrig_type_amount_velocity_ratio_over_14day nameOrig_type_amount_max_velocity_ratio_over_7day nameOrig_type_amount_max_velocity_ratio_over_10day nameOrig_type_amount_max_velocity_ratio_over_14day nameDest_type_txnCount_velocity_ratio_over_7day nameDest_type_txnCount_velocity_ratio_over_10day nameDest_type_txnCount_velocity_ratio_over_14day nameDest_type_amount_velocity_ratio_over_7day nameDest_type_amount_velocity_ratio_over_10day nameDest_type_amount_velocity_ratio_over_14day nameDest_type_amount_max_velocity_ratio_over_7day nameDest_type_amount_max_velocity_ratio_over_10day nameDest_type_amount_max_velocity_ratio_over_14day nameOrig_nameDest_type_txnCount_velocity_ratio_over_7day nameOrig_nameDest_type_txnCount_velocity_ratio_over_10day nameOrig_nameDest_type_txnCount_velocity_ratio_over_14day nameOrig_nameDest_type_amount_velocity_ratio_over_7day nameOrig_nameDest_type_amount_velocity_ratio_over_10day nameOrig_nameDest_type_amount_velocity_ratio_over_14day nameOrig_nameDest_type_amount_max_velocity_ratio_over_7day nameOrig_nameDest_type_amount_max_velocity_ratio_over_10day nameOrig_nameDest_type_amount_max_velocity_ratio_over_14day nameOrig_had_prev_fraud nameDest_had_prev_fraud nameOrig_nameDest_had_prev_fraud nameOrig_type_had_prev_fraud nameDest_type_had_prev_fraud nameOrig_nameDest_type_had_prev_fraud changeBalanceOrg_prcnt changeBalanceDest_prcnt
17 TRANSFER 67277.540 204160.000 136882.460 457734.560 525012.100 1.000 1.000 1.000 1.000 1.000 67277.540 67277.540 67277.540 67277.540 67277.540 0.006 0.004 0.003 400.462 280.323 200.231 67277.540 67277.540 67277.540 1.000 2.000 2.000 2.000 2.000 67277.540 130533.950 130533.950 130533.950 130533.950 0.012 0.008 0.006 776.988 543.891 388.494 67277.540 67277.540 67277.540 1.000 1.000 1.000 1.000 1.000 67277.540 67277.540 67277.540 67277.540 67277.540 0.006 0.004 0.003 400.462 280.323 200.231 67277.540 67277.540 67277.540 1.000 1.000 1.000 1.000 1.000 67277.540 67277.540 67277.540 67277.540 67277.540 0.006 0.004 0.003 400.462 280.323 200.231 67277.540 67277.540 67277.540 1.000 1.000 1.000 1.000 1.000 67277.540 67277.540 67277.540 67277.540 67277.540 0.006 0.004 0.003 400.462 280.323 200.231 67277.540 67277.540 67277.540 1.000 1.000 1.000 1.000 1.000 67277.540 67277.540 67277.540 67277.540 67277.540 0.006 0.004 0.003 400.462 280.323 200.231 67277.540 67277.540 67277.540 0.000 45.000 0.000 0.000 393.000 0.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 84.000 120.000 168.000 86.588 123.697 173.175 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 0.000 0.000 0.000 0.000 0.000 0.000 -32.953 14.698
150 CASH_OUT 16508.840 0.000 0.000 938660.930 955169.770 1.000 1.000 1.000 1.000 1.000 16508.840 16508.840 16508.840 16508.840 16508.840 0.006 0.004 0.003 98.267 68.787 49.133 16508.840 16508.840 16508.840 1.000 1.000 1.000 1.000 1.000 16508.840 16508.840 16508.840 16508.840 16508.840 0.006 0.004 0.003 98.267 68.787 49.133 16508.840 16508.840 16508.840 1.000 1.000 1.000 1.000 1.000 16508.840 16508.840 16508.840 16508.840 16508.840 0.006 0.004 0.003 98.267 68.787 49.133 16508.840 16508.840 16508.840 1.000 1.000 1.000 1.000 1.000 16508.840 16508.840 16508.840 16508.840 16508.840 0.006 0.004 0.003 98.267 68.787 49.133 16508.840 16508.840 16508.840 1.000 1.000 1.000 1.000 1.000 16508.840 16508.840 16508.840 16508.840 16508.840 0.006 0.004 0.003 98.267 68.787 49.133 16508.840 16508.840 16508.840 1.000 1.000 1.000 1.000 1.000 16508.840 16508.840 16508.840 16508.840 16508.840 0.006 0.004 0.003 98.267 68.787 49.133 16508.840 16508.840 16508.840 0.000 364.000 0.000 0.000 456.000 0.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 1.759
169 TRANSFER 493790.130 0.000 0.000 623627.870 1117418.000 1.000 1.000 1.000 1.000 1.000 493790.130 493790.130 493790.130 493790.130 493790.130 0.006 0.004 0.003 2939.227 2057.459 1469.613 493790.130 493790.130 493790.130 1.000 1.000 1.000 1.000 4.000 493790.130 493790.130 493790.130 493790.130 1171692.630 0.006 0.004 0.012 2939.227 2057.459 3487.180 493790.130 493790.130 493790.130 1.000 1.000 1.000 1.000 1.000 493790.130 493790.130 493790.130 493790.130 493790.130 0.006 0.004 0.003 2939.227 2057.459 1469.613 493790.130 493790.130 493790.130 1.000 1.000 1.000 1.000 1.000 493790.130 493790.130 493790.130 493790.130 493790.130 0.006 0.004 0.003 2939.227 2057.459 1469.613 493790.130 493790.130 493790.130 1.000 1.000 1.000 1.000 2.000 493790.130 493790.130 493790.130 493790.130 706914.820 0.006 0.004 0.006 2939.227 2057.459 2103.913 493790.130 493790.130 493790.130 1.000 1.000 1.000 1.000 1.000 493790.130 493790.130 493790.130 493790.130 493790.130 0.006 0.004 0.003 2939.227 2057.459 1469.613 493790.130 493790.130 493790.130 0.000 290.000 0.000 0.000 309.000 0.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 84.000 168.000 240.000 141.602 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 168.000 168.000 240.000 234.701 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 79.180
235 CASH_OUT 382268.420 0.000 0.000 13323843.460 13706111.880 1.000 1.000 1.000 1.000 1.000 382268.420 382268.420 382268.420 382268.420 382268.420 0.006 0.004 0.003 2275.407 1592.785 1137.704 382268.420 382268.420 382268.420 1.000 1.000 1.000 1.000 5.000 382268.420 382268.420 382268.420 382268.420 7591876.780 0.006 0.004 0.015 2275.407 1592.785 22594.871 382268.420 382268.420 4048890.050 1.000 1.000 1.000 1.000 1.000 382268.420 382268.420 382268.420 382268.420 382268.420 0.006 0.004 0.003 2275.407 1592.785 1137.704 382268.420 382268.420 382268.420 1.000 1.000 1.000 1.000 1.000 382268.420 382268.420 382268.420 382268.420 382268.420 0.006 0.004 0.003 2275.407 1592.785 1137.704 382268.420 382268.420 382268.420 1.000 1.000 1.000 1.000 2.000 382268.420 382268.420 382268.420 382268.420 653703.110 0.006 0.004 0.006 2275.407 1592.785 1945.545 382268.420 382268.420 382268.420 1.000 1.000 1.000 1.000 1.000 382268.420 382268.420 382268.420 382268.420 382268.420 0.006 0.004 0.003 2275.407 1592.785 1137.704 382268.420 382268.420 382268.420 0.000 241.000 0.000 0.000 241.000 0.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 67.200 168.000 240.000 16.918 1.000 1.000 0.094 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 168.000 168.000 240.000 196.484 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 2.869
254 DEBIT 2737.510 2720.000 0.000 32886.520 35624.030 1.000 1.000 1.000 1.000 1.000 2737.510 2737.510 2737.510 2737.510 2737.510 0.006 0.004 0.003 16.295 11.406 8.147 2737.510 2737.510 2737.510 1.000 1.000 1.000 1.000 2.000 2737.510 2737.510 2737.510 2737.510 35624.030 0.006 0.004 0.006 16.295 11.406 106.024 2737.510 2737.510 32886.520 1.000 1.000 1.000 1.000 1.000 2737.510 2737.510 2737.510 2737.510 2737.510 0.006 0.004 0.003 16.295 11.406 8.147 2737.510 2737.510 2737.510 1.000 1.000 1.000 1.000 1.000 2737.510 2737.510 2737.510 2737.510 2737.510 0.006 0.004 0.003 16.295 11.406 8.147 2737.510 2737.510 2737.510 1.000 1.000 1.000 1.000 1.000 2737.510 2737.510 2737.510 2737.510 2737.510 0.006 0.004 0.003 16.295 11.406 8.147 2737.510 2737.510 2737.510 1.000 1.000 1.000 1.000 1.000 2737.510 2737.510 2737.510 2737.510 2737.510 0.006 0.004 0.003 16.295 11.406 8.147 2737.510 2737.510 2737.510 0.000 318.000 0.000 0.000 0.000 0.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 168.000 168.000 240.000 25.820 1.000 1.000 0.083 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 0.000 0.000 0.000 0.000 0.000 0.000 -99.963 8.324
In [109]:
categorical_transformed = list(xgb_pipeline.named_steps['preprocess'].transformers_[1][1]\
   .named_steps['one-hot'].get_feature_names(categorical_features))

Function get_feature_names is deprecated; get_feature_names is deprecated in 1.0 and will be removed in 1.2. Please use get_feature_names_out instead.
In [110]:
categorical_transformed
Out[110]:
['type_CASH_IN', 'type_CASH_OUT', 'type_DEBIT', 'type_TRANSFER']
In [111]:
#list(numerical_features)
In [112]:
all_features = np.array(categorical_transformed + list(numerical_features))
all_features = all_features[final_features]
all_features
Out[112]:
array(['type_CASH_IN', 'type_CASH_OUT', 'type_TRANSFER', 'amount',
       'nameOrig_rolling_txn_sum_3day', 'nameOrig_rolling_txn_sum_14day',
       'nameOrig_rolling_txn_count_mean_7day',
       'nameOrig_rolling_txn_amount_max_7day',
       'nameOrig_rolling_txn_amount_max_10day',
       'nameOrig_rolling_txn_amount_max_14day',
       'nameDest_rolling_txn_count_3day',
       'nameDest_rolling_txn_count_10day',
       'nameDest_rolling_txn_sum_3day',
       'nameDest_rolling_txn_count_mean_7day',
       'nameDest_rolling_txn_count_mean_14day',
       'nameDest_rolling_txn_amount_mean_7day',
       'nameDest_rolling_txn_amount_mean_10day',
       'nameOrig_type_rolling_txn_amount_max_7day',
       'nameOrig_type_rolling_txn_amount_max_10day',
       'nameDest_type_rolling_txn_count_7day',
       'nameDest_type_rolling_txn_sum_1day',
       'nameDest_type_rolling_txn_amount_mean_7day',
       'nameOrig_amount_max_velocity_ratio_over_10day',
       'nameDest_txnCount_velocity_ratio_over_7day',
       'nameDest_txnCount_velocity_ratio_over_14day',
       'nameDest_type_txnCount_velocity_ratio_over_7day',
       'nameDest_type_txnCount_velocity_ratio_over_14day',
       'nameOrig_had_prev_fraud', 'nameOrig_nameDest_had_prev_fraud',
       'nameOrig_type_had_prev_fraud',
       'nameOrig_nameDest_type_had_prev_fraud', 'changeBalanceDest_prcnt'],
      dtype='<U59')
In [113]:
# import shap
# 
# model_input = pd.DataFrame(full_processor.fit_transform(x_test))
# model_input.columns = list(numerical_features) + categorical_transformed
# 
# shap_values = shap.TreeExplainer(xgb_model).shap_values(model_input[all_features])
# shap.summary_plot(shap_values, model_input[all_features], max_display=20)#, plot_type="bar")
In [114]:
#np.delete(all_features, [0,1,2,3])
In [115]:
len(x_train.columns)
Out[115]:
188
In [116]:
len(list(numerical_features))
Out[116]:
187
In [117]:
#list(numerical_features) + categorical_transformed
In [118]:
#a = list(numerical_features)
#[x for x in a if x not in x_train.columns]
In [119]:
import shap

#all_features = np.delete(all_features, [0,1,2,3])

x_train = downsampled.drop(['step','isFraud'], axis=1).fillna(0)
#x_train = x_train[all_features]
y_train = downsampled[['isFraud']]

x_train_transform = pd.DataFrame(full_processor.fit_transform(x_train))
x_train_transform.columns = list(numerical_features) + categorical_transformed

#all_features = all_features[final_features]

xgb_model = xgboost.XGBClassifier(subsample=0.8, max_depth=15, learning_rate=0.3, objective= 'binary:logistic',n_jobs=-1,verbosity = 0)
#xgb_pipeline = Pipeline(steps=[('preprocess', full_processor), ('model', xgb_model)])
xgb_model.fit(x_train_transform[all_features], y_train)

model_input = pd.DataFrame(full_processor.fit_transform(x_test.fillna(0)))
model_input.columns = list(numerical_features) + categorical_transformed

shap_values = shap.TreeExplainer(xgb_model).shap_values(model_input[all_features])
shap.summary_plot(shap_values, model_input[all_features], max_display=20)#, plot_type="bar")

ntree_limit is deprecated, use `iteration_range` or model slicing instead.

9. XGB feature importance¶

In [143]:
from xgboost import plot_importance
from matplotlib import pyplot
from matplotlib.pyplot import figure

pyplot.rcParams.update({'font.size': 22})

pyplot.rcParams["figure.figsize"] = (20,12)
figure(figsize=(20, 12), dpi=80)

plot_importance(xgb_model)
plt.xticks(fontsize=18)
plt.yticks(fontsize=18)
plt.title("Feature importance", fontsize=30)
plt.xlabel("Importance score", fontsize=25)
plt.ylabel("Features", fontsize=25)
pyplot.show()

<Figure size 1600x960 with 0 Axes>
In [121]:
len(x_train_transform.columns)
Out[121]:
191
In [122]:
all_features
Out[122]:
array(['type_CASH_IN', 'type_CASH_OUT', 'type_TRANSFER', 'amount',
       'nameOrig_rolling_txn_sum_3day', 'nameOrig_rolling_txn_sum_14day',
       'nameOrig_rolling_txn_count_mean_7day',
       'nameOrig_rolling_txn_amount_max_7day',
       'nameOrig_rolling_txn_amount_max_10day',
       'nameOrig_rolling_txn_amount_max_14day',
       'nameDest_rolling_txn_count_3day',
       'nameDest_rolling_txn_count_10day',
       'nameDest_rolling_txn_sum_3day',
       'nameDest_rolling_txn_count_mean_7day',
       'nameDest_rolling_txn_count_mean_14day',
       'nameDest_rolling_txn_amount_mean_7day',
       'nameDest_rolling_txn_amount_mean_10day',
       'nameOrig_type_rolling_txn_amount_max_7day',
       'nameOrig_type_rolling_txn_amount_max_10day',
       'nameDest_type_rolling_txn_count_7day',
       'nameDest_type_rolling_txn_sum_1day',
       'nameDest_type_rolling_txn_amount_mean_7day',
       'nameOrig_amount_max_velocity_ratio_over_10day',
       'nameDest_txnCount_velocity_ratio_over_7day',
       'nameDest_txnCount_velocity_ratio_over_14day',
       'nameDest_type_txnCount_velocity_ratio_over_7day',
       'nameDest_type_txnCount_velocity_ratio_over_14day',
       'nameOrig_had_prev_fraud', 'nameOrig_nameDest_had_prev_fraud',
       'nameOrig_type_had_prev_fraud',
       'nameOrig_nameDest_type_had_prev_fraud', 'changeBalanceDest_prcnt'],
      dtype='<U59')
In [123]:
list(numerical_features) + categorical_transformed
Out[123]:
['amount',
 'oldbalanceOrg',
 'newbalanceOrig',
 'oldbalanceDest',
 'newbalanceDest',
 'nameOrig_rolling_txn_count_1day',
 'nameOrig_rolling_txn_count_3day',
 'nameOrig_rolling_txn_count_7day',
 'nameOrig_rolling_txn_count_10day',
 'nameOrig_rolling_txn_count_14day',
 'nameOrig_rolling_txn_sum_1day',
 'nameOrig_rolling_txn_sum_3day',
 'nameOrig_rolling_txn_sum_7day',
 'nameOrig_rolling_txn_sum_10day',
 'nameOrig_rolling_txn_sum_14day',
 'nameOrig_rolling_txn_count_mean_7day',
 'nameOrig_rolling_txn_count_mean_10day',
 'nameOrig_rolling_txn_count_mean_14day',
 'nameOrig_rolling_txn_amount_mean_7day',
 'nameOrig_rolling_txn_amount_mean_10day',
 'nameOrig_rolling_txn_amount_mean_14day',
 'nameOrig_rolling_txn_amount_max_7day',
 'nameOrig_rolling_txn_amount_max_10day',
 'nameOrig_rolling_txn_amount_max_14day',
 'nameDest_rolling_txn_count_1day',
 'nameDest_rolling_txn_count_3day',
 'nameDest_rolling_txn_count_7day',
 'nameDest_rolling_txn_count_10day',
 'nameDest_rolling_txn_count_14day',
 'nameDest_rolling_txn_sum_1day',
 'nameDest_rolling_txn_sum_3day',
 'nameDest_rolling_txn_sum_7day',
 'nameDest_rolling_txn_sum_10day',
 'nameDest_rolling_txn_sum_14day',
 'nameDest_rolling_txn_count_mean_7day',
 'nameDest_rolling_txn_count_mean_10day',
 'nameDest_rolling_txn_count_mean_14day',
 'nameDest_rolling_txn_amount_mean_7day',
 'nameDest_rolling_txn_amount_mean_10day',
 'nameDest_rolling_txn_amount_mean_14day',
 'nameDest_rolling_txn_amount_max_7day',
 'nameDest_rolling_txn_amount_max_10day',
 'nameDest_rolling_txn_amount_max_14day',
 'nameOrig_nameDest_rolling_txn_count_1day',
 'nameOrig_nameDest_rolling_txn_count_3day',
 'nameOrig_nameDest_rolling_txn_count_7day',
 'nameOrig_nameDest_rolling_txn_count_10day',
 'nameOrig_nameDest_rolling_txn_count_14day',
 'nameOrig_nameDest_rolling_txn_sum_1day',
 'nameOrig_nameDest_rolling_txn_sum_3day',
 'nameOrig_nameDest_rolling_txn_sum_7day',
 'nameOrig_nameDest_rolling_txn_sum_10day',
 'nameOrig_nameDest_rolling_txn_sum_14day',
 'nameOrig_nameDest_rolling_txn_count_mean_7day',
 'nameOrig_nameDest_rolling_txn_count_mean_10day',
 'nameOrig_nameDest_rolling_txn_count_mean_14day',
 'nameOrig_nameDest_rolling_txn_amount_mean_7day',
 'nameOrig_nameDest_rolling_txn_amount_mean_10day',
 'nameOrig_nameDest_rolling_txn_amount_mean_14day',
 'nameOrig_nameDest_rolling_txn_amount_max_7day',
 'nameOrig_nameDest_rolling_txn_amount_max_10day',
 'nameOrig_nameDest_rolling_txn_amount_max_14day',
 'nameOrig_type_rolling_txn_count_1day',
 'nameOrig_type_rolling_txn_count_3day',
 'nameOrig_type_rolling_txn_count_7day',
 'nameOrig_type_rolling_txn_count_10day',
 'nameOrig_type_rolling_txn_count_14day',
 'nameOrig_type_rolling_txn_sum_1day',
 'nameOrig_type_rolling_txn_sum_3day',
 'nameOrig_type_rolling_txn_sum_7day',
 'nameOrig_type_rolling_txn_sum_10day',
 'nameOrig_type_rolling_txn_sum_14day',
 'nameOrig_type_rolling_txn_count_mean_7day',
 'nameOrig_type_rolling_txn_count_mean_10day',
 'nameOrig_type_rolling_txn_count_mean_14day',
 'nameOrig_type_rolling_txn_amount_mean_7day',
 'nameOrig_type_rolling_txn_amount_mean_10day',
 'nameOrig_type_rolling_txn_amount_mean_14day',
 'nameOrig_type_rolling_txn_amount_max_7day',
 'nameOrig_type_rolling_txn_amount_max_10day',
 'nameOrig_type_rolling_txn_amount_max_14day',
 'nameDest_type_rolling_txn_count_1day',
 'nameDest_type_rolling_txn_count_3day',
 'nameDest_type_rolling_txn_count_7day',
 'nameDest_type_rolling_txn_count_10day',
 'nameDest_type_rolling_txn_count_14day',
 'nameDest_type_rolling_txn_sum_1day',
 'nameDest_type_rolling_txn_sum_3day',
 'nameDest_type_rolling_txn_sum_7day',
 'nameDest_type_rolling_txn_sum_10day',
 'nameDest_type_rolling_txn_sum_14day',
 'nameDest_type_rolling_txn_count_mean_7day',
 'nameDest_type_rolling_txn_count_mean_10day',
 'nameDest_type_rolling_txn_count_mean_14day',
 'nameDest_type_rolling_txn_amount_mean_7day',
 'nameDest_type_rolling_txn_amount_mean_10day',
 'nameDest_type_rolling_txn_amount_mean_14day',
 'nameDest_type_rolling_txn_amount_max_7day',
 'nameDest_type_rolling_txn_amount_max_10day',
 'nameDest_type_rolling_txn_amount_max_14day',
 'nameOrig_nameDest_type_rolling_txn_count_1day',
 'nameOrig_nameDest_type_rolling_txn_count_3day',
 'nameOrig_nameDest_type_rolling_txn_count_7day',
 'nameOrig_nameDest_type_rolling_txn_count_10day',
 'nameOrig_nameDest_type_rolling_txn_count_14day',
 'nameOrig_nameDest_type_rolling_txn_sum_1day',
 'nameOrig_nameDest_type_rolling_txn_sum_3day',
 'nameOrig_nameDest_type_rolling_txn_sum_7day',
 'nameOrig_nameDest_type_rolling_txn_sum_10day',
 'nameOrig_nameDest_type_rolling_txn_sum_14day',
 'nameOrig_nameDest_type_rolling_txn_count_mean_7day',
 'nameOrig_nameDest_type_rolling_txn_count_mean_10day',
 'nameOrig_nameDest_type_rolling_txn_count_mean_14day',
 'nameOrig_nameDest_type_rolling_txn_amount_mean_7day',
 'nameOrig_nameDest_type_rolling_txn_amount_mean_10day',
 'nameOrig_nameDest_type_rolling_txn_amount_mean_14day',
 'nameOrig_nameDest_type_rolling_txn_amount_max_7day',
 'nameOrig_nameDest_type_rolling_txn_amount_max_10day',
 'nameOrig_nameDest_type_rolling_txn_amount_max_14day',
 'nameOrig_time_since_last_txn',
 'nameDest_time_since_last_txn',
 'nameOrig_nameDest_time_since_last_txn',
 'nameOrig_type_time_since_last_txn',
 'nameDest_type_time_since_last_txn',
 'nameOrig_nameDest_type_time_since_last_txn',
 'nameOrig_txnCount_velocity_ratio_over_7day',
 'nameOrig_txnCount_velocity_ratio_over_10day',
 'nameOrig_txnCount_velocity_ratio_over_14day',
 'nameOrig_amount_velocity_ratio_over_7day',
 'nameOrig_amount_velocity_ratio_over_10day',
 'nameOrig_amount_velocity_ratio_over_14day',
 'nameOrig_amount_max_velocity_ratio_over_7day',
 'nameOrig_amount_max_velocity_ratio_over_10day',
 'nameOrig_amount_max_velocity_ratio_over_14day',
 'nameDest_txnCount_velocity_ratio_over_7day',
 'nameDest_txnCount_velocity_ratio_over_10day',
 'nameDest_txnCount_velocity_ratio_over_14day',
 'nameDest_amount_velocity_ratio_over_7day',
 'nameDest_amount_velocity_ratio_over_10day',
 'nameDest_amount_velocity_ratio_over_14day',
 'nameDest_amount_max_velocity_ratio_over_7day',
 'nameDest_amount_max_velocity_ratio_over_10day',
 'nameDest_amount_max_velocity_ratio_over_14day',
 'nameOrig_nameDest_txnCount_velocity_ratio_over_7day',
 'nameOrig_nameDest_txnCount_velocity_ratio_over_10day',
 'nameOrig_nameDest_txnCount_velocity_ratio_over_14day',
 'nameOrig_nameDest_amount_velocity_ratio_over_7day',
 'nameOrig_nameDest_amount_velocity_ratio_over_10day',
 'nameOrig_nameDest_amount_velocity_ratio_over_14day',
 'nameOrig_nameDest_amount_max_velocity_ratio_over_7day',
 'nameOrig_nameDest_amount_max_velocity_ratio_over_10day',
 'nameOrig_nameDest_amount_max_velocity_ratio_over_14day',
 'nameOrig_type_txnCount_velocity_ratio_over_7day',
 'nameOrig_type_txnCount_velocity_ratio_over_10day',
 'nameOrig_type_txnCount_velocity_ratio_over_14day',
 'nameOrig_type_amount_velocity_ratio_over_7day',
 'nameOrig_type_amount_velocity_ratio_over_10day',
 'nameOrig_type_amount_velocity_ratio_over_14day',
 'nameOrig_type_amount_max_velocity_ratio_over_7day',
 'nameOrig_type_amount_max_velocity_ratio_over_10day',
 'nameOrig_type_amount_max_velocity_ratio_over_14day',
 'nameDest_type_txnCount_velocity_ratio_over_7day',
 'nameDest_type_txnCount_velocity_ratio_over_10day',
 'nameDest_type_txnCount_velocity_ratio_over_14day',
 'nameDest_type_amount_velocity_ratio_over_7day',
 'nameDest_type_amount_velocity_ratio_over_10day',
 'nameDest_type_amount_velocity_ratio_over_14day',
 'nameDest_type_amount_max_velocity_ratio_over_7day',
 'nameDest_type_amount_max_velocity_ratio_over_10day',
 'nameDest_type_amount_max_velocity_ratio_over_14day',
 'nameOrig_nameDest_type_txnCount_velocity_ratio_over_7day',
 'nameOrig_nameDest_type_txnCount_velocity_ratio_over_10day',
 'nameOrig_nameDest_type_txnCount_velocity_ratio_over_14day',
 'nameOrig_nameDest_type_amount_velocity_ratio_over_7day',
 'nameOrig_nameDest_type_amount_velocity_ratio_over_10day',
 'nameOrig_nameDest_type_amount_velocity_ratio_over_14day',
 'nameOrig_nameDest_type_amount_max_velocity_ratio_over_7day',
 'nameOrig_nameDest_type_amount_max_velocity_ratio_over_10day',
 'nameOrig_nameDest_type_amount_max_velocity_ratio_over_14day',
 'nameOrig_had_prev_fraud',
 'nameDest_had_prev_fraud',
 'nameOrig_nameDest_had_prev_fraud',
 'nameOrig_type_had_prev_fraud',
 'nameDest_type_had_prev_fraud',
 'nameOrig_nameDest_type_had_prev_fraud',
 'changeBalanceOrg_prcnt',
 'changeBalanceDest_prcnt',
 'type_CASH_IN',
 'type_CASH_OUT',
 'type_DEBIT',
 'type_TRANSFER']
In [124]:
x_train_transform[all_features]
Out[124]:
type_CASH_IN type_CASH_OUT type_TRANSFER amount nameOrig_rolling_txn_sum_3day nameOrig_rolling_txn_sum_14day nameOrig_rolling_txn_count_mean_7day nameOrig_rolling_txn_amount_max_7day nameOrig_rolling_txn_amount_max_10day nameOrig_rolling_txn_amount_max_14day nameDest_rolling_txn_count_3day nameDest_rolling_txn_count_10day nameDest_rolling_txn_sum_3day nameDest_rolling_txn_count_mean_7day nameDest_rolling_txn_count_mean_14day nameDest_rolling_txn_amount_mean_7day nameDest_rolling_txn_amount_mean_10day nameOrig_type_rolling_txn_amount_max_7day nameOrig_type_rolling_txn_amount_max_10day nameDest_type_rolling_txn_count_7day nameDest_type_rolling_txn_sum_1day nameDest_type_rolling_txn_amount_mean_7day nameOrig_amount_max_velocity_ratio_over_10day nameDest_txnCount_velocity_ratio_over_7day nameDest_txnCount_velocity_ratio_over_14day nameDest_type_txnCount_velocity_ratio_over_7day nameDest_type_txnCount_velocity_ratio_over_14day nameOrig_had_prev_fraud nameOrig_nameDest_had_prev_fraud nameOrig_type_had_prev_fraud nameOrig_nameDest_type_had_prev_fraud changeBalanceDest_prcnt
0 0.000 0.000 1.000 331545.250 331545.250 331545.250 1.000 331545.250 331545.250 331545.250 22.000 22.000 5820096.910 22.000 22.000 5820096.910 5820096.910 331545.250 331545.250 3.000 1035942.310 1035942.310 1.000 1.000 1.000 1.000 1.000 0.000 0.000 0.000 0.000 -8.517
1 0.000 1.000 0.000 2806.000 2806.000 2806.000 1.000 2806.000 2806.000 2806.000 1.000 1.000 2806.000 1.000 1.000 2806.000 2806.000 2806.000 2806.000 1.000 2806.000 2806.000 1.000 1.000 1.000 1.000 1.000 0.000 0.000 0.000 0.000 -99.996
2 0.000 1.000 0.000 681093.570 681093.570 681093.570 1.000 681093.570 681093.570 681093.570 22.000 22.000 5820096.910 22.000 22.000 5820096.910 5820096.910 681093.570 681093.570 8.000 2144626.800 2144626.800 1.000 1.000 1.000 1.000 1.000 0.000 0.000 0.000 0.000 67.296
3 1.000 0.000 0.000 273305.730 273305.730 273305.730 1.000 273305.730 273305.730 273305.730 22.000 22.000 5820096.910 22.000 22.000 5820096.910 5820096.910 273305.730 273305.730 11.000 2639527.800 2639527.800 1.000 1.000 1.000 1.000 1.000 0.000 0.000 0.000 0.000 14.095
4 0.000 1.000 0.000 14949.840 14949.840 14949.840 0.500 14949.840 14949.840 14949.840 3.000 3.000 23087.160 1.500 1.500 11543.580 11543.580 14949.840 14949.840 1.000 14949.840 7474.920 1.000 2.000 2.000 2.000 2.000 0.000 0.000 0.000 0.000 82.310
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
8257 1.000 0.000 0.000 50763.620 50763.620 50763.620 0.006 50763.620 50763.620 50763.620 1.000 1.000 50763.620 0.006 0.009 302.164 211.515 50763.620 50763.620 1.000 50763.620 302.164 1.000 168.000 112.000 168.000 168.000 0.000 0.000 0.000 0.000 -77.554
8258 0.000 0.000 1.000 898178.600 898178.600 898178.600 0.006 898178.600 898178.600 898178.600 1.000 1.000 898178.600 0.006 0.003 5346.301 3742.411 898178.600 898178.600 1.000 898178.600 5346.301 1.000 168.000 336.000 168.000 336.000 0.000 0.000 0.000 0.000 89817860.000
8259 0.000 1.000 0.000 114888.200 114888.200 114888.200 0.006 114888.200 114888.200 114888.200 1.000 1.000 114888.200 0.006 0.003 683.858 478.701 114888.200 114888.200 1.000 114888.200 683.858 1.000 168.000 336.000 168.000 336.000 0.000 0.000 0.000 0.000 97.334
8260 1.000 0.000 0.000 288119.030 288119.030 288119.030 0.006 288119.030 288119.030 288119.030 1.000 2.000 288119.030 0.006 0.018 1714.994 1230.342 288119.030 288119.030 1.000 288119.030 1714.994 1.000 168.000 56.000 168.000 84.000 0.000 0.000 0.000 0.000 -8.373
8261 0.000 1.000 0.000 6961359.110 6961359.110 6961359.110 0.006 6961359.110 6961359.110 6961359.110 1.000 3.000 6961359.110 0.006 0.021 41436.661 29736.029 6961359.110 6961359.110 1.000 6961359.110 41436.661 1.000 168.000 48.000 168.000 67.200 0.000 0.000 0.000 0.000 401.348

8262 rows × 32 columns

In [125]:
#sample_ind = 20
#shap.plots.waterfall(shap_values[20], max_display=14)
In [126]:
model_input[all_features]
Out[126]:
type_CASH_IN type_CASH_OUT type_TRANSFER amount nameOrig_rolling_txn_sum_3day nameOrig_rolling_txn_sum_14day nameOrig_rolling_txn_count_mean_7day nameOrig_rolling_txn_amount_max_7day nameOrig_rolling_txn_amount_max_10day nameOrig_rolling_txn_amount_max_14day nameDest_rolling_txn_count_3day nameDest_rolling_txn_count_10day nameDest_rolling_txn_sum_3day nameDest_rolling_txn_count_mean_7day nameDest_rolling_txn_count_mean_14day nameDest_rolling_txn_amount_mean_7day nameDest_rolling_txn_amount_mean_10day nameOrig_type_rolling_txn_amount_max_7day nameOrig_type_rolling_txn_amount_max_10day nameDest_type_rolling_txn_count_7day nameDest_type_rolling_txn_sum_1day nameDest_type_rolling_txn_amount_mean_7day nameOrig_amount_max_velocity_ratio_over_10day nameDest_txnCount_velocity_ratio_over_7day nameDest_txnCount_velocity_ratio_over_14day nameDest_type_txnCount_velocity_ratio_over_7day nameDest_type_txnCount_velocity_ratio_over_14day nameOrig_had_prev_fraud nameOrig_nameDest_had_prev_fraud nameOrig_type_had_prev_fraud nameOrig_nameDest_type_had_prev_fraud changeBalanceDest_prcnt
0 0.000 0.000 1.000 67277.540 67277.540 67277.540 0.006 67277.540 67277.540 67277.540 2.000 2.000 130533.950 0.012 0.006 776.988 543.891 67277.540 67277.540 1.000 67277.540 400.462 1.000 84.000 168.000 168.000 336.000 0.000 0.000 0.000 0.000 14.698
1 0.000 1.000 0.000 16508.840 16508.840 16508.840 0.006 16508.840 16508.840 16508.840 1.000 1.000 16508.840 0.006 0.003 98.267 68.787 16508.840 16508.840 1.000 16508.840 98.267 1.000 168.000 336.000 168.000 336.000 0.000 0.000 0.000 0.000 1.759
2 0.000 0.000 1.000 493790.130 493790.130 493790.130 0.006 493790.130 493790.130 493790.130 1.000 1.000 493790.130 0.006 0.012 2939.227 2057.459 493790.130 493790.130 1.000 493790.130 2939.227 1.000 168.000 84.000 168.000 168.000 0.000 0.000 0.000 0.000 79.180
3 0.000 1.000 0.000 382268.420 382268.420 382268.420 0.006 382268.420 382268.420 382268.420 1.000 1.000 382268.420 0.006 0.015 2275.407 1592.785 382268.420 382268.420 1.000 382268.420 2275.407 1.000 168.000 67.200 168.000 168.000 0.000 0.000 0.000 0.000 2.869
4 0.000 0.000 0.000 2737.510 2737.510 2737.510 0.006 2737.510 2737.510 2737.510 1.000 1.000 2737.510 0.006 0.006 16.295 11.406 2737.510 2737.510 1.000 2737.510 16.295 1.000 168.000 168.000 168.000 336.000 0.000 0.000 0.000 0.000 8.324
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
1370 1.000 0.000 0.000 40488.480 40488.480 40488.480 0.006 40488.480 40488.480 40488.480 1.000 2.000 40488.480 0.012 0.018 894.051 625.836 40488.480 40488.480 2.000 40488.480 894.051 1.000 84.000 56.000 84.000 112.000 0.000 0.000 0.000 0.000 -3.555
1371 0.000 1.000 0.000 304772.540 304772.540 304772.540 0.006 304772.540 304772.540 304772.540 1.000 1.000 304772.540 0.006 0.006 1814.122 1269.886 304772.540 304772.540 1.000 304772.540 1814.122 1.000 168.000 168.000 168.000 168.000 0.000 0.000 0.000 0.000 98.074
1372 0.000 1.000 0.000 425236.800 425236.800 425236.800 0.006 425236.800 425236.800 425236.800 1.000 1.000 425236.800 0.006 0.006 2531.171 1771.820 425236.800 425236.800 1.000 425236.800 2531.171 1.000 168.000 168.000 168.000 168.000 0.000 0.000 0.000 0.000 23.239
1373 1.000 0.000 0.000 128654.360 128654.360 128654.360 0.006 128654.360 128654.360 128654.360 2.000 2.000 1128618.730 0.012 0.015 6717.969 4702.578 128654.360 128654.360 1.000 128654.360 765.800 1.000 168.000 134.400 168.000 336.000 0.000 0.000 0.000 0.000 -1.373
1374 0.000 1.000 0.000 799123.570 799123.570 799123.570 0.006 799123.570 799123.570 799123.570 1.000 1.000 799123.570 0.006 0.009 4756.688 3329.682 799123.570 799123.570 1.000 799123.570 4756.688 1.000 168.000 112.000 168.000 112.000 0.000 0.000 0.000 0.000 14.598

1375 rows × 32 columns

10. Model explainability¶

In [127]:
#shap.plots.beeswarm(shap_values)
In [128]:
X5000 = shap.utils.sample(model_input[all_features], 5000)
explainer_ebm = shap.Explainer(xgb_model.predict, X5000)
shap_values_ebm = explainer_ebm(model_input[all_features])

Permutation explainer: 1376it [00:57, 19.35it/s]
In [129]:
shap.plots.beeswarm(shap_values_ebm, max_display=25)
In [130]:
x_test = x_test.reset_index(drop=True)
x_test[['type','amount','nameOrig_had_prev_fraud','nameOrig_nameDest_had_prev_fraud','nameOrig_nameDest_type_had_prev_fraud']].iloc[34:35,]
Out[130]:
type amount nameOrig_had_prev_fraud nameOrig_nameDest_had_prev_fraud nameOrig_nameDest_type_had_prev_fraud
34 CASH_OUT 10000000.000 0.000 0.000 0.000
In [131]:
model_input.iloc[34:35,]
Out[131]:
amount oldbalanceOrg newbalanceOrig oldbalanceDest newbalanceDest nameOrig_rolling_txn_count_1day nameOrig_rolling_txn_count_3day nameOrig_rolling_txn_count_7day nameOrig_rolling_txn_count_10day nameOrig_rolling_txn_count_14day nameOrig_rolling_txn_sum_1day nameOrig_rolling_txn_sum_3day nameOrig_rolling_txn_sum_7day nameOrig_rolling_txn_sum_10day nameOrig_rolling_txn_sum_14day nameOrig_rolling_txn_count_mean_7day nameOrig_rolling_txn_count_mean_10day nameOrig_rolling_txn_count_mean_14day nameOrig_rolling_txn_amount_mean_7day nameOrig_rolling_txn_amount_mean_10day nameOrig_rolling_txn_amount_mean_14day nameOrig_rolling_txn_amount_max_7day nameOrig_rolling_txn_amount_max_10day nameOrig_rolling_txn_amount_max_14day nameDest_rolling_txn_count_1day nameDest_rolling_txn_count_3day nameDest_rolling_txn_count_7day nameDest_rolling_txn_count_10day nameDest_rolling_txn_count_14day nameDest_rolling_txn_sum_1day nameDest_rolling_txn_sum_3day nameDest_rolling_txn_sum_7day nameDest_rolling_txn_sum_10day nameDest_rolling_txn_sum_14day nameDest_rolling_txn_count_mean_7day nameDest_rolling_txn_count_mean_10day nameDest_rolling_txn_count_mean_14day nameDest_rolling_txn_amount_mean_7day nameDest_rolling_txn_amount_mean_10day nameDest_rolling_txn_amount_mean_14day nameDest_rolling_txn_amount_max_7day nameDest_rolling_txn_amount_max_10day nameDest_rolling_txn_amount_max_14day nameOrig_nameDest_rolling_txn_count_1day nameOrig_nameDest_rolling_txn_count_3day nameOrig_nameDest_rolling_txn_count_7day nameOrig_nameDest_rolling_txn_count_10day nameOrig_nameDest_rolling_txn_count_14day nameOrig_nameDest_rolling_txn_sum_1day nameOrig_nameDest_rolling_txn_sum_3day nameOrig_nameDest_rolling_txn_sum_7day nameOrig_nameDest_rolling_txn_sum_10day nameOrig_nameDest_rolling_txn_sum_14day nameOrig_nameDest_rolling_txn_count_mean_7day nameOrig_nameDest_rolling_txn_count_mean_10day nameOrig_nameDest_rolling_txn_count_mean_14day nameOrig_nameDest_rolling_txn_amount_mean_7day nameOrig_nameDest_rolling_txn_amount_mean_10day nameOrig_nameDest_rolling_txn_amount_mean_14day nameOrig_nameDest_rolling_txn_amount_max_7day nameOrig_nameDest_rolling_txn_amount_max_10day nameOrig_nameDest_rolling_txn_amount_max_14day nameOrig_type_rolling_txn_count_1day nameOrig_type_rolling_txn_count_3day nameOrig_type_rolling_txn_count_7day nameOrig_type_rolling_txn_count_10day nameOrig_type_rolling_txn_count_14day nameOrig_type_rolling_txn_sum_1day nameOrig_type_rolling_txn_sum_3day nameOrig_type_rolling_txn_sum_7day nameOrig_type_rolling_txn_sum_10day nameOrig_type_rolling_txn_sum_14day nameOrig_type_rolling_txn_count_mean_7day nameOrig_type_rolling_txn_count_mean_10day nameOrig_type_rolling_txn_count_mean_14day nameOrig_type_rolling_txn_amount_mean_7day nameOrig_type_rolling_txn_amount_mean_10day nameOrig_type_rolling_txn_amount_mean_14day nameOrig_type_rolling_txn_amount_max_7day nameOrig_type_rolling_txn_amount_max_10day nameOrig_type_rolling_txn_amount_max_14day nameDest_type_rolling_txn_count_1day nameDest_type_rolling_txn_count_3day nameDest_type_rolling_txn_count_7day nameDest_type_rolling_txn_count_10day nameDest_type_rolling_txn_count_14day nameDest_type_rolling_txn_sum_1day nameDest_type_rolling_txn_sum_3day nameDest_type_rolling_txn_sum_7day nameDest_type_rolling_txn_sum_10day nameDest_type_rolling_txn_sum_14day nameDest_type_rolling_txn_count_mean_7day nameDest_type_rolling_txn_count_mean_10day nameDest_type_rolling_txn_count_mean_14day nameDest_type_rolling_txn_amount_mean_7day nameDest_type_rolling_txn_amount_mean_10day nameDest_type_rolling_txn_amount_mean_14day nameDest_type_rolling_txn_amount_max_7day nameDest_type_rolling_txn_amount_max_10day nameDest_type_rolling_txn_amount_max_14day nameOrig_nameDest_type_rolling_txn_count_1day nameOrig_nameDest_type_rolling_txn_count_3day nameOrig_nameDest_type_rolling_txn_count_7day nameOrig_nameDest_type_rolling_txn_count_10day nameOrig_nameDest_type_rolling_txn_count_14day nameOrig_nameDest_type_rolling_txn_sum_1day nameOrig_nameDest_type_rolling_txn_sum_3day nameOrig_nameDest_type_rolling_txn_sum_7day nameOrig_nameDest_type_rolling_txn_sum_10day nameOrig_nameDest_type_rolling_txn_sum_14day nameOrig_nameDest_type_rolling_txn_count_mean_7day nameOrig_nameDest_type_rolling_txn_count_mean_10day nameOrig_nameDest_type_rolling_txn_count_mean_14day nameOrig_nameDest_type_rolling_txn_amount_mean_7day nameOrig_nameDest_type_rolling_txn_amount_mean_10day nameOrig_nameDest_type_rolling_txn_amount_mean_14day nameOrig_nameDest_type_rolling_txn_amount_max_7day nameOrig_nameDest_type_rolling_txn_amount_max_10day nameOrig_nameDest_type_rolling_txn_amount_max_14day nameOrig_time_since_last_txn nameDest_time_since_last_txn nameOrig_nameDest_time_since_last_txn nameOrig_type_time_since_last_txn nameDest_type_time_since_last_txn nameOrig_nameDest_type_time_since_last_txn nameOrig_txnCount_velocity_ratio_over_7day nameOrig_txnCount_velocity_ratio_over_10day nameOrig_txnCount_velocity_ratio_over_14day nameOrig_amount_velocity_ratio_over_7day nameOrig_amount_velocity_ratio_over_10day nameOrig_amount_velocity_ratio_over_14day nameOrig_amount_max_velocity_ratio_over_7day nameOrig_amount_max_velocity_ratio_over_10day nameOrig_amount_max_velocity_ratio_over_14day nameDest_txnCount_velocity_ratio_over_7day nameDest_txnCount_velocity_ratio_over_10day nameDest_txnCount_velocity_ratio_over_14day nameDest_amount_velocity_ratio_over_7day nameDest_amount_velocity_ratio_over_10day nameDest_amount_velocity_ratio_over_14day nameDest_amount_max_velocity_ratio_over_7day nameDest_amount_max_velocity_ratio_over_10day nameDest_amount_max_velocity_ratio_over_14day nameOrig_nameDest_txnCount_velocity_ratio_over_7day nameOrig_nameDest_txnCount_velocity_ratio_over_10day nameOrig_nameDest_txnCount_velocity_ratio_over_14day nameOrig_nameDest_amount_velocity_ratio_over_7day nameOrig_nameDest_amount_velocity_ratio_over_10day nameOrig_nameDest_amount_velocity_ratio_over_14day nameOrig_nameDest_amount_max_velocity_ratio_over_7day nameOrig_nameDest_amount_max_velocity_ratio_over_10day nameOrig_nameDest_amount_max_velocity_ratio_over_14day nameOrig_type_txnCount_velocity_ratio_over_7day nameOrig_type_txnCount_velocity_ratio_over_10day nameOrig_type_txnCount_velocity_ratio_over_14day nameOrig_type_amount_velocity_ratio_over_7day nameOrig_type_amount_velocity_ratio_over_10day nameOrig_type_amount_velocity_ratio_over_14day nameOrig_type_amount_max_velocity_ratio_over_7day nameOrig_type_amount_max_velocity_ratio_over_10day nameOrig_type_amount_max_velocity_ratio_over_14day nameDest_type_txnCount_velocity_ratio_over_7day nameDest_type_txnCount_velocity_ratio_over_10day nameDest_type_txnCount_velocity_ratio_over_14day nameDest_type_amount_velocity_ratio_over_7day nameDest_type_amount_velocity_ratio_over_10day nameDest_type_amount_velocity_ratio_over_14day nameDest_type_amount_max_velocity_ratio_over_7day nameDest_type_amount_max_velocity_ratio_over_10day nameDest_type_amount_max_velocity_ratio_over_14day nameOrig_nameDest_type_txnCount_velocity_ratio_over_7day nameOrig_nameDest_type_txnCount_velocity_ratio_over_10day nameOrig_nameDest_type_txnCount_velocity_ratio_over_14day nameOrig_nameDest_type_amount_velocity_ratio_over_7day nameOrig_nameDest_type_amount_velocity_ratio_over_10day nameOrig_nameDest_type_amount_velocity_ratio_over_14day nameOrig_nameDest_type_amount_max_velocity_ratio_over_7day nameOrig_nameDest_type_amount_max_velocity_ratio_over_10day nameOrig_nameDest_type_amount_max_velocity_ratio_over_14day nameOrig_had_prev_fraud nameDest_had_prev_fraud nameOrig_nameDest_had_prev_fraud nameOrig_type_had_prev_fraud nameDest_type_had_prev_fraud nameOrig_nameDest_type_had_prev_fraud changeBalanceOrg_prcnt changeBalanceDest_prcnt type_CASH_IN type_CASH_OUT type_DEBIT type_TRANSFER
34 10000000.000 10000000.000 0.000 2517892.180 12517892.180 1.000 1.000 1.000 1.000 1.000 10000000.000 10000000.000 10000000.000 10000000.000 10000000.000 0.006 0.004 0.003 59523.810 41666.667 29761.905 10000000.000 10000000.000 10000000.000 1.000 1.000 1.000 1.000 2.000 10000000.000 10000000.000 10000000.000 10000000.000 10337036.090 0.006 0.004 0.006 59523.810 41666.667 30764.988 10000000.000 10000000.000 10000000.000 1.000 1.000 1.000 1.000 1.000 10000000.000 10000000.000 10000000.000 10000000.000 10000000.000 0.006 0.004 0.003 59523.810 41666.667 29761.905 10000000.000 10000000.000 10000000.000 1.000 1.000 1.000 1.000 1.000 10000000.000 10000000.000 10000000.000 10000000.000 10000000.000 0.006 0.004 0.003 59523.810 41666.667 29761.905 10000000.000 10000000.000 10000000.000 1.000 1.000 1.000 1.000 1.000 10000000.000 10000000.000 10000000.000 10000000.000 10000000.000 0.006 0.004 0.003 59523.810 41666.667 29761.905 10000000.000 10000000.000 10000000.000 1.000 1.000 1.000 1.000 1.000 10000000.000 10000000.000 10000000.000 10000000.000 10000000.000 0.006 0.004 0.003 59523.810 41666.667 29761.905 10000000.000 10000000.000 10000000.000 0.000 317.000 0.000 0.000 362.000 0.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 168.000 168.000 240.000 325.045 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 0.000 0.000 0.000 0.000 0.000 0.000 -100.000 397.157 0.000 1.000 0.000 0.000
In [132]:
#xgb_model.predict(model_input)
In [133]:
shap.plots.beeswarm(shap_values_ebm, max_display=33)
In [134]:
shap_values_ebm[34]
Out[134]:
.values =
array([ 9.37500000e-03,  1.83750000e-01, -4.37500000e-03,  7.55625000e-01,
        0.00000000e+00,  0.00000000e+00,  0.00000000e+00,  0.00000000e+00,
        0.00000000e+00,  0.00000000e+00,  0.00000000e+00,  3.12500000e-03,
       -1.25000000e-03,  2.50000000e-03, -1.25000000e-03,  1.25000000e-03,
       -5.00000000e-03,  0.00000000e+00,  0.00000000e+00,  0.00000000e+00,
        1.30104261e-18,  4.68750000e-02,  0.00000000e+00, -6.25000000e-04,
       -3.75000000e-03,  0.00000000e+00, -1.25000000e-03,  0.00000000e+00,
        0.00000000e+00,  0.00000000e+00,  0.00000000e+00, -2.50000000e-02])

.base_values =
0.04

.data =
array([0.00000000e+00, 1.00000000e+00, 0.00000000e+00, 1.00000000e+07,
       1.00000000e+07, 1.00000000e+07, 5.95238095e-03, 1.00000000e+07,
       1.00000000e+07, 1.00000000e+07, 1.00000000e+00, 1.00000000e+00,
       1.00000000e+07, 5.95238095e-03, 5.95238095e-03, 5.95238095e+04,
       4.16666667e+04, 1.00000000e+07, 1.00000000e+07, 1.00000000e+00,
       1.00000000e+07, 5.95238095e+04, 1.00000000e+00, 1.68000000e+02,
       1.68000000e+02, 1.68000000e+02, 3.36000000e+02, 0.00000000e+00,
       0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 3.97157436e+02])
In [135]:
x_test.iloc[34:35,:][['amount','type','nameDest_rolling_txn_sum_14day','changeBalanceDest_prcnt','nameDest_rolling_txn_count_7day']]
Out[135]:
amount type nameDest_rolling_txn_sum_14day changeBalanceDest_prcnt nameDest_rolling_txn_count_7day
34 10000000.000 CASH_OUT 10337036.090 397.157 1.000
In [136]:
xgb_model.predict(model_input[all_features])[34]
Out[136]:
1
In [137]:
shap.plots.waterfall(shap_values_ebm[34])
In [138]:
shap_values_ebm
Out[138]:
.values =
array([[ 0.      , -0.008125,  0.01875 , ...,  0.      ,  0.      ,
        -0.015   ],
       [ 0.      ,  0.01875 , -0.00875 , ...,  0.      ,  0.      ,
        -0.008125],
       [ 0.014375, -0.01625 ,  0.055   , ...,  0.      ,  0.      ,
        -0.098125],
       ...,
       [ 0.0025  ,  0.016875, -0.008125, ...,  0.      ,  0.      ,
        -0.015625],
       [-0.00875 , -0.00625 , -0.005625, ...,  0.      ,  0.      ,
         0.005   ],
       [ 0.080625,  0.160625, -0.004375, ...,  0.      ,  0.      ,
        -0.0475  ]])

.base_values =
array([0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04])

.data =
array([[ 0.        ,  0.        ,  1.        , ...,  0.        ,
         0.        , 14.69790549],
       [ 0.        ,  1.        ,  0.        , ...,  0.        ,
         0.        ,  1.75876314],
       [ 0.        ,  0.        ,  1.        , ...,  0.        ,
         0.        , 79.1801268 ],
       ...,
       [ 0.        ,  1.        ,  0.        , ...,  0.        ,
         0.        , 23.23866238],
       [ 1.        ,  0.        ,  0.        , ...,  0.        ,
         0.        , -1.37347746],
       [ 0.        ,  1.        ,  0.        , ...,  0.        ,
         0.        , 14.59774664]])
In [139]:
y_test = y_test.reset_index(drop=True)
y_test[y_test['isFraud'] == 1]
Out[139]:
isFraud
29 1
34 1
83 1
154 1
189 1
229 1
239 1
253 1
264 1
389 1
411 1
457 1
603 1
664 1
670 1
675 1
702 1
714 1
716 1
739 1
751 1
777 1
821 1
897 1
966 1
1008 1
1065 1
1081 1
1086 1
1177 1
1233 1
1247 1
1279 1
1374 1
In [141]:
test.iloc[34:35,]
Out[141]:
step type amount oldbalanceOrg newbalanceOrig oldbalanceDest newbalanceDest isFraud nameOrig_rolling_txn_count_1day nameOrig_rolling_txn_count_3day nameOrig_rolling_txn_count_7day nameOrig_rolling_txn_count_10day nameOrig_rolling_txn_count_14day nameOrig_rolling_txn_sum_1day nameOrig_rolling_txn_sum_3day nameOrig_rolling_txn_sum_7day nameOrig_rolling_txn_sum_10day nameOrig_rolling_txn_sum_14day nameOrig_rolling_txn_count_mean_7day nameOrig_rolling_txn_count_mean_10day nameOrig_rolling_txn_count_mean_14day nameOrig_rolling_txn_amount_mean_7day nameOrig_rolling_txn_amount_mean_10day nameOrig_rolling_txn_amount_mean_14day nameOrig_rolling_txn_amount_max_7day nameOrig_rolling_txn_amount_max_10day nameOrig_rolling_txn_amount_max_14day nameDest_rolling_txn_count_1day nameDest_rolling_txn_count_3day nameDest_rolling_txn_count_7day nameDest_rolling_txn_count_10day nameDest_rolling_txn_count_14day nameDest_rolling_txn_sum_1day nameDest_rolling_txn_sum_3day nameDest_rolling_txn_sum_7day nameDest_rolling_txn_sum_10day nameDest_rolling_txn_sum_14day nameDest_rolling_txn_count_mean_7day nameDest_rolling_txn_count_mean_10day nameDest_rolling_txn_count_mean_14day nameDest_rolling_txn_amount_mean_7day nameDest_rolling_txn_amount_mean_10day nameDest_rolling_txn_amount_mean_14day nameDest_rolling_txn_amount_max_7day nameDest_rolling_txn_amount_max_10day nameDest_rolling_txn_amount_max_14day nameOrig_nameDest_rolling_txn_count_1day nameOrig_nameDest_rolling_txn_count_3day nameOrig_nameDest_rolling_txn_count_7day nameOrig_nameDest_rolling_txn_count_10day nameOrig_nameDest_rolling_txn_count_14day nameOrig_nameDest_rolling_txn_sum_1day nameOrig_nameDest_rolling_txn_sum_3day nameOrig_nameDest_rolling_txn_sum_7day nameOrig_nameDest_rolling_txn_sum_10day nameOrig_nameDest_rolling_txn_sum_14day nameOrig_nameDest_rolling_txn_count_mean_7day nameOrig_nameDest_rolling_txn_count_mean_10day nameOrig_nameDest_rolling_txn_count_mean_14day nameOrig_nameDest_rolling_txn_amount_mean_7day nameOrig_nameDest_rolling_txn_amount_mean_10day nameOrig_nameDest_rolling_txn_amount_mean_14day nameOrig_nameDest_rolling_txn_amount_max_7day nameOrig_nameDest_rolling_txn_amount_max_10day nameOrig_nameDest_rolling_txn_amount_max_14day nameOrig_type_rolling_txn_count_1day nameOrig_type_rolling_txn_count_3day nameOrig_type_rolling_txn_count_7day nameOrig_type_rolling_txn_count_10day nameOrig_type_rolling_txn_count_14day nameOrig_type_rolling_txn_sum_1day nameOrig_type_rolling_txn_sum_3day nameOrig_type_rolling_txn_sum_7day nameOrig_type_rolling_txn_sum_10day nameOrig_type_rolling_txn_sum_14day nameOrig_type_rolling_txn_count_mean_7day nameOrig_type_rolling_txn_count_mean_10day nameOrig_type_rolling_txn_count_mean_14day nameOrig_type_rolling_txn_amount_mean_7day nameOrig_type_rolling_txn_amount_mean_10day nameOrig_type_rolling_txn_amount_mean_14day nameOrig_type_rolling_txn_amount_max_7day nameOrig_type_rolling_txn_amount_max_10day nameOrig_type_rolling_txn_amount_max_14day nameDest_type_rolling_txn_count_1day nameDest_type_rolling_txn_count_3day nameDest_type_rolling_txn_count_7day nameDest_type_rolling_txn_count_10day nameDest_type_rolling_txn_count_14day nameDest_type_rolling_txn_sum_1day nameDest_type_rolling_txn_sum_3day nameDest_type_rolling_txn_sum_7day nameDest_type_rolling_txn_sum_10day nameDest_type_rolling_txn_sum_14day nameDest_type_rolling_txn_count_mean_7day nameDest_type_rolling_txn_count_mean_10day nameDest_type_rolling_txn_count_mean_14day nameDest_type_rolling_txn_amount_mean_7day nameDest_type_rolling_txn_amount_mean_10day nameDest_type_rolling_txn_amount_mean_14day nameDest_type_rolling_txn_amount_max_7day nameDest_type_rolling_txn_amount_max_10day nameDest_type_rolling_txn_amount_max_14day nameOrig_nameDest_type_rolling_txn_count_1day nameOrig_nameDest_type_rolling_txn_count_3day nameOrig_nameDest_type_rolling_txn_count_7day nameOrig_nameDest_type_rolling_txn_count_10day nameOrig_nameDest_type_rolling_txn_count_14day nameOrig_nameDest_type_rolling_txn_sum_1day nameOrig_nameDest_type_rolling_txn_sum_3day nameOrig_nameDest_type_rolling_txn_sum_7day nameOrig_nameDest_type_rolling_txn_sum_10day nameOrig_nameDest_type_rolling_txn_sum_14day nameOrig_nameDest_type_rolling_txn_count_mean_7day nameOrig_nameDest_type_rolling_txn_count_mean_10day nameOrig_nameDest_type_rolling_txn_count_mean_14day nameOrig_nameDest_type_rolling_txn_amount_mean_7day nameOrig_nameDest_type_rolling_txn_amount_mean_10day nameOrig_nameDest_type_rolling_txn_amount_mean_14day nameOrig_nameDest_type_rolling_txn_amount_max_7day nameOrig_nameDest_type_rolling_txn_amount_max_10day nameOrig_nameDest_type_rolling_txn_amount_max_14day nameOrig_time_since_last_txn nameDest_time_since_last_txn nameOrig_nameDest_time_since_last_txn nameOrig_type_time_since_last_txn nameDest_type_time_since_last_txn nameOrig_nameDest_type_time_since_last_txn nameOrig_txnCount_velocity_ratio_over_7day nameOrig_txnCount_velocity_ratio_over_10day nameOrig_txnCount_velocity_ratio_over_14day nameOrig_amount_velocity_ratio_over_7day nameOrig_amount_velocity_ratio_over_10day nameOrig_amount_velocity_ratio_over_14day nameOrig_amount_max_velocity_ratio_over_7day nameOrig_amount_max_velocity_ratio_over_10day nameOrig_amount_max_velocity_ratio_over_14day nameDest_txnCount_velocity_ratio_over_7day nameDest_txnCount_velocity_ratio_over_10day nameDest_txnCount_velocity_ratio_over_14day nameDest_amount_velocity_ratio_over_7day nameDest_amount_velocity_ratio_over_10day nameDest_amount_velocity_ratio_over_14day nameDest_amount_max_velocity_ratio_over_7day nameDest_amount_max_velocity_ratio_over_10day nameDest_amount_max_velocity_ratio_over_14day nameOrig_nameDest_txnCount_velocity_ratio_over_7day nameOrig_nameDest_txnCount_velocity_ratio_over_10day nameOrig_nameDest_txnCount_velocity_ratio_over_14day nameOrig_nameDest_amount_velocity_ratio_over_7day nameOrig_nameDest_amount_velocity_ratio_over_10day nameOrig_nameDest_amount_velocity_ratio_over_14day nameOrig_nameDest_amount_max_velocity_ratio_over_7day nameOrig_nameDest_amount_max_velocity_ratio_over_10day nameOrig_nameDest_amount_max_velocity_ratio_over_14day nameOrig_type_txnCount_velocity_ratio_over_7day nameOrig_type_txnCount_velocity_ratio_over_10day nameOrig_type_txnCount_velocity_ratio_over_14day nameOrig_type_amount_velocity_ratio_over_7day nameOrig_type_amount_velocity_ratio_over_10day nameOrig_type_amount_velocity_ratio_over_14day nameOrig_type_amount_max_velocity_ratio_over_7day nameOrig_type_amount_max_velocity_ratio_over_10day nameOrig_type_amount_max_velocity_ratio_over_14day nameDest_type_txnCount_velocity_ratio_over_7day nameDest_type_txnCount_velocity_ratio_over_10day nameDest_type_txnCount_velocity_ratio_over_14day nameDest_type_amount_velocity_ratio_over_7day nameDest_type_amount_velocity_ratio_over_10day nameDest_type_amount_velocity_ratio_over_14day nameDest_type_amount_max_velocity_ratio_over_7day nameDest_type_amount_max_velocity_ratio_over_10day nameDest_type_amount_max_velocity_ratio_over_14day nameOrig_nameDest_type_txnCount_velocity_ratio_over_7day nameOrig_nameDest_type_txnCount_velocity_ratio_over_10day nameOrig_nameDest_type_txnCount_velocity_ratio_over_14day nameOrig_nameDest_type_amount_velocity_ratio_over_7day nameOrig_nameDest_type_amount_velocity_ratio_over_10day nameOrig_nameDest_type_amount_velocity_ratio_over_14day nameOrig_nameDest_type_amount_max_velocity_ratio_over_7day nameOrig_nameDest_type_amount_max_velocity_ratio_over_10day nameOrig_nameDest_type_amount_max_velocity_ratio_over_14day nameOrig_had_prev_fraud nameDest_had_prev_fraud nameOrig_nameDest_had_prev_fraud nameOrig_type_had_prev_fraud nameDest_type_had_prev_fraud nameOrig_nameDest_type_had_prev_fraud changeBalanceOrg_prcnt changeBalanceDest_prcnt
2582 718 CASH_OUT 10000000.000 10000000.000 0.000 2517892.180 12517892.180 1 1.000 1.000 1.000 1.000 1.000 10000000.000 10000000.000 10000000.000 10000000.000 10000000.000 0.006 0.004 0.003 59523.810 41666.667 29761.905 10000000.000 10000000.000 10000000.000 1.000 1.000 1.000 1.000 2.000 10000000.000 10000000.000 10000000.000 10000000.000 10337036.090 0.006 0.004 0.006 59523.810 41666.667 30764.988 10000000.000 10000000.000 10000000.000 1.000 1.000 1.000 1.000 1.000 10000000.000 10000000.000 10000000.000 10000000.000 10000000.000 0.006 0.004 0.003 59523.810 41666.667 29761.905 10000000.000 10000000.000 10000000.000 1.000 1.000 1.000 1.000 1.000 10000000.000 10000000.000 10000000.000 10000000.000 10000000.000 0.006 0.004 0.003 59523.810 41666.667 29761.905 10000000.000 10000000.000 10000000.000 1.000 1.000 1.000 1.000 1.000 10000000.000 10000000.000 10000000.000 10000000.000 10000000.000 0.006 0.004 0.003 59523.810 41666.667 29761.905 10000000.000 10000000.000 10000000.000 1.000 1.000 1.000 1.000 1.000 10000000.000 10000000.000 10000000.000 10000000.000 10000000.000 0.006 0.004 0.003 59523.810 41666.667 29761.905 10000000.000 10000000.000 10000000.000 NaN 317.000 NaN NaN 362.000 NaN 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 168.000 168.000 240.000 325.045 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 168.000 240.000 336.000 168.000 240.000 336.000 1.000 1.000 1.000 NaN 0.000 NaN NaN 0.000 NaN -100.000 397.157

Appendix¶

In [142]:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

from mpl_toolkits.mplot3d import Axes3D
from sklearn.datasets import load_breast_cancer
from sklearn.decomposition import PCA
from sklearn import datasets
from sklearn.preprocessing import StandardScaler
# %matplotlib notebook

pyplot.rcParams["figure.figsize"] = (40,12)

X = x_train_transform
y = y_train
target_names = ['isNotFraud','isFraud']

pca = PCA(n_components=2)
X_r = pca.fit(X).transform(X)

# Percentage of variance explained for each components
print(
    "explained variance ratio (first two components): %s"
    % str(pca.explained_variance_ratio_)
)

plt.figure()
colors = ["navy", "turquoise", "darkorange"]
lw = 2

for color, i, target_name in zip(colors, [0, 1, 2], target_names):
    plt.scatter(
        X_r[:,0], X_r[:,1], color=color, alpha=0.8, lw=lw, label=target_name
    )
plt.legend(loc="best", shadow=False, scatterpoints=1)

explained variance ratio (first two components): [0.71268147 0.16490853]
Out[142]:
<matplotlib.legend.Legend at 0x7fd6117dfa00>

End¶