def algorithmAutomat(algorithm, X_train, y_train, X_test, name):
    algDict = {}
    train_s = time.time()
    algorithm.fit(X_train, y_train)
    train_e = time.time()
    pred_s = time.time()
    y_pred = algorithm.predict_proba(X_test)
    pred_e = time.time()
    algDict = algorithmCurvesInfo(name, y_pred, y_test)
    algDict['train_time'] = round((train_e - train_s), 2)
    algDict['predict_time'] = round((pred_e - pred_s), 2)
    algDict['model'] = algorithm
    print((name + ' Prediction calculated'))
    print((('Elapsed time: ' + str(round((pred_e - train_s), 2))) + ' seconds'))
    return algDict
def algorithmAutomat(algorithm, X_train, y_train, X_test, name):
    algDict = {}
    train_s = time.time()
    algorithm.fit(X_train, y_train)
    train_e = time.time()
    pred_s = time.time()
    y_pred = algorithm.predict_proba(X_test)
    pred_e = time.time()
    algDict = algorithmCurvesInfo(name, y_pred, y_test)
    algDict['train_time'] = round((train_e - train_s), 2)
    algDict['predict_time'] = round((pred_e - pred_s), 2)
    algDict['model'] = algorithm
    print((name + ' Prediction calculated'))
    print((('Elapsed time: ' + str(round((pred_e - train_s), 2))) + ' seconds'))
    return algDict