Kaggle competition: Histopathologic Cancer Detection
<SOS> metric: AUC Kaggle data source: histopathologic-cancer-detection<categorify>
sigmoid = lambda x:scipy.special.expit(x )
status_du=pd.get_dummies(new_data['status'] )<concatenate>
sub1 = pd.read_csv('.. /input/blending-power-0-9754/sub.csv')
 sub2 = pd.read_csv('.. /input/tta-power-densenet169/submission_tta_64.csv')
 sub3 = pd.read_csv('.. /input/you-really-need-attention-pytorch/sub_tta.csv' )
new_data=pd.concat([new_data,status_du],axis=1)
<drop_column>
sub1.label =(sub1.label + sub2.label + sub3.label)/ 3
new_data=new_data.drop(['status'],axis=1)
 new_data.head()<drop_column>
sub1.to_csv('ensemble.csv', index=False )