create_models.py

def create_models(seed=2):
    '''
    Create a list of machine learning models.

            Parameters:
                    seed (integer): random seed of the models

            Returns:
                    models (list): list containing the models
    '''

    models = []
    models.append(('dummy_classifier', DummyClassifier(random_state=seed, strategy='most_frequent')))
    models.append(('k_nearest_neighbors', KNeighborsClassifier()))
    models.append(('logistic_regression', LogisticRegression(random_state=seed)))
    models.append(('support_vector_machines', SVC(random_state=seed)))
    models.append(('random_forest', RandomForestClassifier(random_state=seed)))
    models.append(('gradient_boosting', GradientBoostingClassifier(random_state=seed)))
    
    return models

# create a list with all the algorithms we are going to assess
models = create_models()