#validation acc 구하기
estimator = KerasClassifier(build_fn=create_deep_learning_model, epochs=5, batch_size=5)
kfold = StratifiedKFold(n_splits=5, shuffle=True, random_state=seed)
results = cross_val_score(estimator, x_train_res, y_train_res, cv=kfold)
model_acc = results.mean()*100
print("Results: %.2f%% (%.2f%%)" % (model_acc, results.std()*100))
#confustion matrix구하기
y_pred = cross_val_predict(estimator, x_train_res, y_train_res, cv=kfold)
validation_acc = y_pred.mean()*100
print(input_name)
print("Results: %.2f%% (%.2f%%)" % (validation_acc, y_pred.std()*100))
conf_mat = confusion_matrix(y_train_res, y_pred)
print(conf_mat)
print()
model_acc를 confustion matrix로 구하면 되겠네?!
시간 절약~