Linear regression, Ridge, Lasso, Elastic net. Polynomial features

Linear regression

from sklearn.linear_model import LinearRegression
model = LinearRegression()
model.fit(X_train,y_train)
predictions = model.predict(X_test)

Ridge, Lasso, Elastic net

from sklearn.linear_model import Ridge
from sklearn.linear_model import Lasso
from sklearn.linear_model import ElasticNet

and with cross-validation:

from sklearn.linear_model import RidgeCV
from sklearn.linear_model import LassoCV
from sklearn.linear_model import ElasticNetCV

Adding polynomial features to the data

from sklearn.preprocessing import PolynomialFeatures
polynomial_converter = PolynomialFeatures(degree=2,include_bias=False)
polynomial_converter.fit_transform(X)