STAT 140B (STAT 196M): Statisical Learning

Slides

Slides are based on Introduction to Statistical Learning by James, Witten, Hastie, And Tibshirani.

Original RMarkdown files available upon request.

Chapter 2: Statistical Learning

• 2.1 What is Statistical Learning?
• 2.2 Assessing Model Accuracy

Chapter 3: Linear Regression

• 3.1 (Simple) Linear Regression
• 3.2 Multiple Linear Regression
• 3.3 Other Considerations in the Regression Model

Chapter 4: Classification

• 4.1 and 4.2 Introducing Classification
• 4.3 Logistic Regression
• 4.4 Generative Models for Classification
  • 4.4.1 Linear Discriminant Analysis for p = 1
  • 4.4.2 Linear Discriminant Analysis for p > 2
  • 4.4.3 Quadratic Discriminant Analysis
  • 4.4.4 Naive Bayes
• 4.6 Generalized Linear Models

Chapter 5: Resampling Methods

• 5.1 Cross-Validation
• 5.2 Bootstrap (slides from Dr. James Flegal, UCR)
  • Original rmd with R code

Chapter 6: Linear Model Selection and Regularization

• Slides (from ISLR2 resources).

Chapter 7: Moving Beyond Linearity

• Slides (from ISLR2 resources).
  • Slides 1-15

Chapter 8: Tree-Based Methods

• Slides (from ISLR2 resources).