elif (model_name == 'coxregression'): if data_name == 'maggic': model.fit(Train_All, duration_col='days_to_fu', event_col='death_all') Predict = model.predict_partial_hazard(X_test) elif (data_name == 'heart_trans' or 'heart_wait'): model.fit(Train_All, duration_col="'Survival'", event_col="'Censor'") Predict = model.predict_partial_hazard(X_test) else: model.fit(X_train, Y_train) Predict = model.predict_proba(X_test)[:, 1] # Performance AUC_ar[j][k] = metrics.roc_auc_score(Y_test, Predict) AUPRC_ar[j][k] = metrics.average_precision_score(Y_test, Predict) Cind_ar[j][k] = C_index(Y_test, Predict) #%% Output = np.zeros([L, 6]) for j in range(L): Output[j, 0] = round(np.mean(AUC_ar[j]), 4) Output[j, 1] = round((2 * np.std(AUC_ar[j]) / np.sqrt(num_folds)), 4) Output[j, 2] = round(np.mean(AUPRC_ar[j]), 4) Output[j, 3] = round((2 * np.std(AUPRC_ar[j]) / np.sqrt(num_folds)), 4)