Imbalanced Data article

default_confusion.py

hardpredtst=gbc.predict(Xtest)
def conf_matrix(y,pred):
    ((tn, fp), (fn, tp)) = metrics.confusion_matrix(y, pred)
    ((tnr,fpr),(fnr,tpr))= metrics.confusion_matrix(y, pred, normalize='true')
    return pd.DataFrame([[f'TN = {tn} (TNR = {tnr:1.2%})', f'FP = {fp} (FPR = {fpr:1.2%})'], # 97
                         [f'FN = {fn} (FNR = {fnr:1.2%})', f'TP = {tp} (TPR = {tpr:1.2%})']],#96
            index=['True 0(Legit)', 'True 1(Fraud)'], 
            columns=['Pred 0(Approve as Legit)', 'Pred 1(Deny as Fraud)'])
conf_matrix(ytest,hardpredtst)