Part 2. Forecasting numeric values with regression

This part of the book, chapters 8 and 9, covers regression. Regression is a continuation of supervised learning from chapters 1 through 7. Recall that supervised learning is machine learning when we have a target variable, or something we want to predict. The difference between regression and classification is that in regression our target variable is numeric and continuous.

Chapter 8 covers an introduction to linear regression, locally weighted linear regression, and shrinkage methods. Chapter 9 takes some ideas from tree building in chapter 3 and applies these to regression to create tree-based regression.

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