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)
