# Ceteris Lab downloadable Python script
# Course: Fundamentals of Python for Financial Econometrics

import numpy as np
from sklearn.linear_model import RidgeCV, LassoCV
rng=np.random.default_rng(32); X=rng.normal(size=(500,30)); b=np.zeros(30); b[:5]=[2,-1.5,1,.5,.3]; y=X@b+rng.normal(size=500)
print('ridge alpha',RidgeCV(alphas=np.logspace(-3,3,40)).fit(X,y).alpha_)
print('lasso alpha',LassoCV(cv=5,random_state=1).fit(X,y).alpha_)