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Computational Intelligence and Feature Selection: Rough and Fuzzy Approaches (Repost)

Posted By: step778
Computational Intelligence and Feature Selection: Rough and Fuzzy Approaches (Repost)

Richard Jensen, Qiang Shen, "Computational Intelligence and Feature Selection: Rough and Fuzzy Approaches"
2008 | pages: 345 | ISBN: 0470229756 | PDF | 3,3 mb

The rough and fuzzy set approaches presented here open up manynew frontiers for continued research and development
Computational Intelligence and Feature Selection providesreaders with the background and fundamental ideas behind FeatureSelection (FS), with an emphasis on techniques based on rough andfuzzy sets. For readers who are less familiar with the subject, thebook begins with an introduction to fuzzy set theory andfuzzy-rough set theory. Building on this foundation, the bookprovides:
- A critical review of FS methods, with particular emphasis ontheir current limitations
- Program files implementing major algorithms, together with thenecessary instructions and datasets, available on a related Website
- Coverage of the background and fundamental ideas behind FS
- A systematic presentation of the leading methods reviewed in aconsistent algorithmic framework
- Real-world applications with worked examples that illustrate thepower and efficacy of the FS approaches covered
- An investigation of the associated areas of FS, including ruleinduction and clustering methods using hybridizations of fuzzy andrough set theories
Computational Intelligence and Feature Selection is anideal resource for advanced undergraduates, postgraduates,researchers, and professional engineers. However, itsstraightforward presentation of the underlying concepts makes thebook meaningful to specialists and nonspecialists alike.

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