imports

import pandas as pd
import numpy as np
import sklearn
import pickle 
import time 
import datetime
import warnings
warnings.filterwarnings('ignore')

%run ../function_proposed_gcn.py

with open('../fraudTrain.pkl', 'rb') as file:
    fraudTrain = pickle.load(file)

fraudTrain.is_fraud.mean()

0.005727773406766326

df_results = try_6(fraudTrain, 0.052,1e7,0.8)
df_results = try_6(fraudTrain, 0.054,1e7,0.8, prev_results=df_results)
df_results = try_6(fraudTrain, 0.056,1e7,0.8, prev_results=df_results)
df_results = try_6(fraudTrain, 0.058,1e7,0.8, prev_results=df_results)
ymdhms = datetime.datetime.fromtimestamp(time.time()).strftime('%Y%m%d-%H%M%S') 
df_results.to_csv(f'../results/{ymdhms}-proposed.csv',index=False)

df_results

	model	time	acc	pre	rec	f1	auc	graph_based	method	throw_rate	train_size	train_cols	train_frate	test_size	test_frate	hyper_params	theta	gamma
0	GCN	None	0.960831	0.692698	0.452019	0.547056	0.972166	True	Proposed	0.052	86625	amt	0.051890	28875	0.052329	None	10000000.0	0.8
1	GCN	None	0.969143	0.761484	0.594483	0.667699	0.982588	True	Proposed	0.054	83416	amt	0.054618	27806	0.052147	None	10000000.0	0.8
2	GCN	None	0.964047	0.758494	0.540930	0.631498	0.981711	True	Proposed	0.056	80437	amt	0.055683	26813	0.056950	None	10000000.0	0.8
3	GCN	None	0.956621	0.698658	0.448939	0.546629	0.972666	True	Proposed	0.058	77664	amt	0.057916	25888	0.058251	None	10000000.0	0.8

df_results = try_6(fraudTrain, 0.06,1e7,0.8)
df_results = try_6(fraudTrain, 0.062,1e7,0.8, prev_results=df_results)
df_results = try_6(fraudTrain, 0.064,1e7,0.8, prev_results=df_results)
df_results = try_6(fraudTrain, 0.066, 1e7,0.8, prev_results=df_results)
df_results = try_6(fraudTrain, 0.068,1e7,0.8, prev_results=df_results)
ymdhms = datetime.datetime.fromtimestamp(time.time()).strftime('%Y%m%d-%H%M%S') 
df_results.to_csv(f'../results/{ymdhms}-proposed.csv',index=False)

df_results

df_results = try_6(fraudTrain, 0.07,1e7,0.8)
df_results = try_6(fraudTrain, 0.072,1e7,0.8, prev_results=df_results)
df_results = try_6(fraudTrain, 0.074,1e7,0.8, prev_results=df_results)
df_results = try_6(fraudTrain, 0.076,1e7,0.8, prev_results=df_results)
df_results = try_6(fraudTrain, 0.078,1e7,0.8, prev_results=df_results)
ymdhms = datetime.datetime.fromtimestamp(time.time()).strftime('%Y%m%d-%H%M%S') 
df_results.to_csv(f'../results/{ymdhms}-proposed.csv',index=False)

df_results

df_results = try_6(fraudTrain, 0.08,1e7,0.8)
df_results = try_6(fraudTrain, 0.082,1e7,0.8, prev_results=df_results)
df_results = try_6(fraudTrain, 0.084,1e7,0.8, prev_results=df_results)
df_results = try_6(fraudTrain, 0.086,1e7,0.8, prev_results=df_results)
df_results = try_6(fraudTrain, 0.088,1e7,0.8, prev_results=df_results)
ymdhms = datetime.datetime.fromtimestamp(time.time()).strftime('%Y%m%d-%H%M%S') 
df_results.to_csv(f'../results/{ymdhms}-proposed.csv',index=False)

df_results

df_results = try_6(fraudTrain, 0.09,1e7,0.8)
df_results = try_6(fraudTrain, 0.092,1e7,0.8, prev_results=df_results)
df_results = try_6(fraudTrain, 0.094,1e7,0.8, prev_results=df_results)
df_results = try_6(fraudTrain, 0.096,1e7,0.8, prev_results=df_results)
df_results = try_6(fraudTrain, 0.098,1e7,0.8, prev_results=df_results)
ymdhms = datetime.datetime.fromtimestamp(time.time()).strftime('%Y%m%d-%H%M%S') 
df_results.to_csv(f'../results/{ymdhms}-proposed.csv',index=False)

df_results

df_results = try_6(fraudTrain, 0.00573,1e7,0.8)
ymdhms = datetime.datetime.fromtimestamp(time.time()).strftime('%Y%m%d-%H%M%S') 
df_results.to_csv(f'../results/{ymdhms}-proposed.csv',index=False)

df_results