Kaggle competition: IEEE-CIS Fraud Detection
mean = [0.485, 0.456, 0.406]
std = [0.229, 0.224, 0.225]
normalize_transform = Normalize(mean, std )<set_options>
sub1 = pd.read_csv('.. /input/stacking/stack_median.csv')
 sub2 = pd.read_csv('.. /input/stacking-higher-and-higher/stack_median.csv')
 sub3 = pd.read_csv('.. /input/ensemble/submission_p2_1.csv')
 sub4 = pd.read_csv('.. /input/safe-box/blend02.csv')
 sample = pd.read_csv('.. /input/ieee-fraud-detection/sample_submission.csv' )
<load_pretrained><EOS> 
sample['isFraud'] =(0.35*sub1['isFraud'] + 0.30*sub2['isFraud'] + 0.25*sub3['isFraud'] + 0.10*sub4['isFraud'])
 sample.to_csv('All_Blends.csv', index=False )