Limit search to available items
Book Cover

Title Feature selection for data and pattern recognition / Urszula Stańczyk, Lakhmi C. Jain, editors
Published Heidelberg : Springer, 2015
Online access available from:
Springer eBooks    View Resource Record  


Description 1 online resource (xviii, 355 pages) : illustrations (some color)
Series Studies in Computational Intelligence, 1860-949X ; volume 584
Studies in computational intelligence ; 584. 1860-949X
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
Summary 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
Bibliography Includes bibliographical references and index
Subject Pattern recognition systems.
Rough sets.
Form Electronic book
Author Stańczyk, Urszula, editor
Jain, L. C., editor
ISBN 3662456192 (print)
3662456206 (electronic bk.)
9783662456194 (print)
9783662456200 (electronic bk.)