Chapter 21: Feature Selection
This chapter introduces feature selection, i.e., finding a well-performing, hopefully small set of features for a task.
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Chapter 21.01: Introduction
We motivate feature selection and discuss the difference to feature extraction.
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Chapter 21.02: Motivating Examples
In this section, we explain the practical importance of feature selection and show that models with integrated selection do not always work.
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Chapter 21.03: Filter Methods I
We introduce how filter methods work and how they can be used for feature selection.
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Chapter 21.04: Filter Methods II (Examples and Caveats)
In this section, we discuss how filter methods can be misleading and show how they work in practical applications.
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Chapter 21.05: Wrapper Methods
This section explains wrapper methods and explains how they can aid feature selection.
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Chapter 21.06: Literature
Download »chapter-literature-feature-selection.pdf«