Machine Learning, Decision Tree, Random Forest, Adaboost, Gradient Boosting.
shrinking coefficients to zero ❌ Selected features will be biased ✧ Prediction can be worse than Ridge Ridge Regression (L2) ✅ Prevents overfitting ❌ Increases bias ✧ Less interpretability AdaBoost ✅ Fast ✧ Reduced bias ✧ Little need to tune ❌ Vulnerable to noise ✧ Can overfit Gradient Boosting ✅