Be the first to like this
* linear models: logistic regression
* polynomial decision rule and polynomial regression
* SVM (Support Vector Machine), kernel trick
* Overfitting: two definitions
* Model selection
* Regularization: L1, L2, elastic net.
* Decision trees
* splitting criteria for classification and regression
* overfitting in trees: pre-stopping and post-pruning
* non-stability of trees
* feature importance
* RSM, subsampling, bagging.
* Random Forest