Feature Selection for Data and Pattern Recognition

Nonfiction, Computers, Advanced Computing, Artificial Intelligence, General Computing
Cover of the book Feature Selection for Data and Pattern Recognition by , Springer Berlin Heidelberg
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Author: ISBN: 9783662456200
Publisher: Springer Berlin Heidelberg Publication: December 30, 2014
Imprint: Springer Language: English
Author:
ISBN: 9783662456200
Publisher: Springer Berlin Heidelberg
Publication: December 30, 2014
Imprint: Springer
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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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