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Feature Selection for Data and Pattern Recognition

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 act...

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Bibliographic Details
Other Authors: Stańczyk, Urszula (Editor), Jain, Lakhmi C. (Editor)
Format: eBook
Language:English
Published: Berlin, Heidelberg Springer Berlin Heidelberg 2015, 2015
Edition:1st ed. 2015
Series:Studies in Computational Intelligence
Subjects:
Computational Intelligence
Artificial Intelligence
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
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520 |a 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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