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13.4.4 Sequential Feature Selection (L13: Feature Selection)

Sebastian's books: https://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: https://sebastianraschka.com/pdf/lect... 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. https://www.sciencedirect.com/science... ------- This video is part of my Introduction of Machine Learning course. Next video:    • 13.4.5 Sequential Feature Selection -...   The complete playlist:    • Intro to Machine Learning and Statist...   A handy overview page with links to the materials: https://sebastianraschka.com/blog/202... ------- If you want to be notified about future videos, please consider subscribing to my channel:    / sebastianraschka