Kaggle competition: IEEE-CIS Fraud Detection
final_predictions = cnn_model.predict(mnist_test_array)
 prediction_test_array = []
for i in final_predictions:
prediction_test_array.append(np.argmax(i))<save_to_csv>
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')
 sub5 = pd.read_csv('.. /input/stackers-blend-top-4/All_Blends.csv')
 sample = pd.read_csv('.. /input/ieee-fraud-detection/sample_submission.csv' )
submission = pd.DataFrame({
'ImageId': test_df_org.index+1,
'Label': prediction_test_array
})
 submission.to_csv('final_submission.csv', index=False )<set_options>
sample['isFraud'] =(0.35*sub1['isFraud'] + 0.30*sub2['isFraud'] + 0.25*sub3['isFraud'] + 0.15*sub4['isFraud'] + 0.15*sub5['isFraud'])
 sample.to_csv('submission.csv', index=False )