Feature Selection for Data and Pattern Recognition by Urszula StaåczykFeature Selection for Data and Pattern Recognition by Urszula Staåczyk

Feature Selection for Data and Pattern Recognition

byUrszula StaåczykEditorLakhmi C. Jain

Hardcover | January 15, 2015

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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.

Title:Feature Selection for Data and Pattern RecognitionFormat:HardcoverDimensions:355 pages, 23.5 × 15.5 × 0.03 inPublished:January 15, 2015Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:3662456192

ISBN - 13:9783662456194

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Table of Contents

Feature Selection for Data and Pattern Recogniton: an Introduction.- Part I Estimation of Feature Importance.- Part II Rough Set Approach to Attribute Reduction.- Part III Rule Discovery and Evaluation.- Part IV Data- and Domain-oriented Methodologies.

Editorial 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)