Kaggle competition: IEEE-CIS Fraud Detection
<SOS> metric: AUC Kaggle data source: ieee-cis-fraud-detection<feature_engineering>
import os
import numpy as np
import pandas as pd
submission_df["label"] = 0.65*submission_df_resnext["label"] + 0.35*submission_df_xception["label"]<save_to_csv>
sub_path = ".. /input/ieeesubmissions4"
all_files = os.listdir(sub_path)
 all_files
<set_options><EOS> 
all_blends = pd.read_csv(os.path.join(sub_path, 'All_Blends_9430.csv'), index_col=0)
 stack_median = pd.read_csv(os.path.join(sub_path, 'stack_median_9424.csv'), index_col=0)
 sub = stack_median.copy()
sub.head()
sub['isFraud'] = stack_median['isFraud'].values*0.156+all_blends['isFraud'].values*0.844
sub['isFraud'].head()
sub.head()
sub.to_csv('blend_of_blends.csv', float_format='%.6f' )