13.4.4 Sequential Feature Selection (L13: Feature Selection) @SebastianRaschka
13.4.4 Sequential Feature Selection (L13: Feature Selection)  @SebastianRaschka
Uploaded January 2022 | Updated September 2026, 2 weeks ago
Sebastian's books: sebastianraschka.com/books

This video explains how sequential feature selection works. Sequential feature selection is a wrapper method for feature selection that uses the performance (e.g., accuracy) of a classifier to select good feature subsets in an iterative fashion. You can think of sequential feature selection method as an efficient approximation to an exhaustive feature subset search.

Slides: sebastianraschka.com/pdf/lecture-notes/stat451fs21/13_feat-sele__slides.pdf

Sequential feature selection paper: Ferri, F. J., Pudil P., Hatef, M., Kittler, J. (1994). "Comparative study of techniques for large-scale feature selection." Pattern Recognition in Practice IV : 403-413. sciencedirect.com/science/article/pii/B9780444818928500407

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This video is part of my Introduction of Machine Learning course.

Next video: youtube.com/watch?v=KYypVSwqqHI&list=PLTKMiZHVd_2KyGirGEvKlniaWeLOHhUF3&index=95

The complete playlist: youtube.com/playlist?list=PLTKMiZHVd_2KyGirGEvKlniaWeLOHhUF3

A handy overview page with links to the materials: sebastianraschka.com/blog/2021/ml-course.html

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13.4.4 Sequential Feature Selection (L13: Feature Selection)

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