PSL_Book
1. Introduction
2. Linear Regression
3. Variable Selection and Regularization
4. Regression Trees and Ensemble
5. Nonlinear Regression
6. Clustering Analysis
7. Latent Structure Models
7.1. Model-based Clustering
7.2. Mixture Models
7.3. The EM Algorithm
7.4. Latent Dirichlet Allocation Model
7.5. Hidden Markov Models
8. TBA
9. Discriminant Analysis
10. Logistic Regression
11. Support Vector Machine
12. Classification Trees and Boosting
13. Recommender System
PSL_Book
7.
Latent Structure Models
7.
Latent Structure Models
7.1. Model-based Clustering
7.2. Mixture Models
7.3. The EM Algorithm
7.4. Latent Dirichlet Allocation Model
7.5. Hidden Markov Models