Regression and Classification

The videos below cover the material on Regression and Classification from Chapter 12 of the book. See here for the full YouTube playlist. Click on the titles to download the slides.

Linear MMSE estimation

Ordinary least squares

Explained variance

Coefficient error

Training error

Test error

Ridge regression

Sparse regression

Logistic regression

Softmax regression

Regression trees

Classification trees

Bagging, random forests, boosting

Neural networks

Evaluating classification

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    • Probability
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    • Continuous Variables
    • Multiple Discrete Variables
    • Multiple Continuous Variables
    • Discrete and Continuous
    • Averaging
    • Correlation
    • Estimation of Population Parameters
    • Hypothesis Testing
    • PCA and Low-Rank Models
    • Regression and Classification
    • Causal Inference
  • Code
    • Probability
    • Discrete Variables
    • Continuous Variables
    • Multiple Discrete Variables
    • Multiple Continuous Variables
    • Discrete and Continuous
    • Averaging
    • Correlation
    • Estimation of Population Parameters
    • Hypothesis Testing
    • PCA and Low-Rank Models
    • Regression and Classification
  • Solutions

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