Regularisation
Overview
1. Introduction
2. Application
3. EDA
4. Learning Process
5. Bias-Variance Tradeoff
6. Regression (review)
7. Classification
8. Validation
9. Regularisation
10. Clustering
11. Evaluation
12. Deployment
13. Ethics
Lecture outline
●Variable subset selection
○Best subset selection
○Stepwise selection methods - forward, backward, hybrid
●Shrinkage methods
○Ridge regression
○Lasso
○Elastic net
●Dimension reduction
○Principal components analysis and regression
●Considerations in high dimensions
Best subset selection
Example data