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Feature Selection for Data and Pattern Recognition

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Feature Selection for Data and Pattern Recognition Synopsis

This research book provides the reader with a selection of high-quality texts dedicated to current progress, new developments and research trends in feature selection for data and pattern recognition.

Even though it has been the subject of interest for some time, feature selection remains one of actively pursued avenues of investigations due to its importance and bearing upon other problems and tasks.

This volume points to a number of advances topically subdivided into four parts: estimation of importance of characteristic features, their relevance, dependencies, weighting and ranking; rough set approach to attribute reduction with focus on relative reducts; construction of rules and their evaluation; and data- and domain-oriented methodologies.

About This Edition

ISBN: 9783662456194
Publication date:
Author: Urszula StaÔnczyk, L C Jain
Publisher: Springer an imprint of Springer Berlin Heidelberg
Format: Hardback
Pagination: 355 pages
Series: Studies in Computational Intelligence
Genres: Artificial intelligence