PSL_Book
  • 1. Introduction
    • 1.1. Introduction to statistical learning
    • 1.2. Least squares vs. nearest neighbors
      • 1.2.1. Introduction to LS and kNN
      • 1.2.2. Simulation Study
      • 1.2.3. Compute Bayes rule
      • 1.2.4. Discussion
  • 2. Linear Regression
  • 3. Variable Selection and Regularization
  • 4. Regression Trees and Ensemble
  • 5. Nonlinear Regression
  • 6. Clustering Analysis
  • 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
  • 1. Introduction
  • 1.2. Least squares vs. nearest neighbors

1.2. Least squares vs. nearest neighbors

  • 1.2.1. Introduction to LS and kNN
  • 1.2.2. Simulation Study
  • 1.2.3. Compute Bayes rule
  • 1.2.4. Discussion
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