Overview
- Recent research trends in feature selection for data and pattern recognition
- 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
- Presents approaches in feature selection for data and pattern classification using computational intelligence paradigms
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Computational Intelligence (SCI, volume 584)
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About this book
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.
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Keywords
Table of contents (14 chapters)
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Front Matter
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Estimation of Feature Importance
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Front Matter
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Rough Set Approach to Attribute Reduction
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Front Matter
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Rule Discovery and Evaluation
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Front Matter
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Data- and Domain-Oriented Methodologies
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Front Matter
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Back Matter
Reviews
“The content of the book is outstanding from the point of view of the novelty of the exposed methods, the clarity of the discourse, and the variety of the illustrative examples. … The book is aimed at researchers and practitioners in the domains of machine learning, computer science, data mining, statistical pattern recognition, and bioinformatics.” (L. State, Computing Reviews, June, 2015)
Editors and Affiliations
Bibliographic Information
Book Title: Feature Selection for Data and Pattern Recognition
Editors: Urszula Stańczyk, Lakhmi C. Jain
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-662-45620-0
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2015
Hardcover ISBN: 978-3-662-45619-4Published: 15 January 2015
Softcover ISBN: 978-3-662-50845-9Published: 24 September 2016
eBook ISBN: 978-3-662-45620-0Published: 30 December 2014
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XVIII, 355
Number of Illustrations: 54 b/w illustrations, 20 illustrations in colour