PSL_Book
1. Introduction
2. Linear Regression
3. Variable Selection and Regularization
4. Regression Trees and Ensemble
5. Nonlinear Regression
6. Clustering Analysis
6.1. Distance Measures
6.2. K-means and K-medoids
6.3. Choice of K
6.4. Hierarchical Clustering
6.5. R/Python Code
7. Latent Structure Models
8. TBA
9. Discriminant Analysis
10. Logistic Regression
11. Support Vector Machine
12. Classification Trees and Boosting
13. Recommender System
PSL_Book
6.
Clustering Analysis
6.
Clustering Analysis
6.1. Distance Measures
6.2. K-means and K-medoids
6.3. Choice of K
6.4. Hierarchical Clustering
6.5. R/Python Code