View elastic_net.py
| from sklearn.linear_model import ElasticNet | |
| elastic_net = ElasticNet(alpha=0.1, l1_ratio=0.5, random_state=42) | |
| elastic_net.fit(X, y) |
View lasso_regression.py
| from sklearn.linear_model import Lasso | |
| lasso_reg = Lasso(alpha=0.1) | |
| lasso_reg.fit(X, y) |
View ridge_regression.py
| from sklearn.linear_model import Ridge | |
| ridge_reg = Ridge(alpha=1, solver="cholesky", random_state=42) | |
| ridge_reg.fit(X, y) | |
| # 'cholesky' is a matrix factorixation techinque used in the closed form equation |