Machine Learning, Decision Tree, Random Forest, Adaboost, Gradient Boosting.
well with large data sets — cost of calculating distance is high ✧ Needs feature scaling ✧ Doesn’t work well on imbalanced data ✧ Doesn’t deal well with missing values Decision Tree ✅ Doesn’t require standardization or normalization ✧ Easy to implement ✧ Can handle missing values ✧ Automatic