Lasso Regression, Ridge Regression, L1 Regularization, L2 Regularization.
Preferable when feature selection is crucial and a sparse model is desired. Ridge: Suitable when all features should be retained, and multicollinearity is a concern. CODE import numpy as np import matplotlib.pyplot as plt from sklearn.datasets import load_diabetes from sklearn.linear_model import