baseline_models.py

# prepare for modeling
X_train = train.drop(['id', 'target'], axis=1)
y_train = train['target']

X_test = test.drop(['id'], axis=1)

# scaling data
scaler = StandardScaler()
X_train = scaler.fit_transform(X_train)
X_test = scaler.transform(X_test)

# define models
ridge = linear_model.Ridge()
lasso = linear_model.Lasso()
elastic = linear_model.ElasticNet()
lasso_lars = linear_model.LassoLars()
bayesian_ridge = linear_model.BayesianRidge()
logistic = linear_model.LogisticRegression(solver='liblinear')
sgd = linear_model.SGDClassifier()