Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications / by Muhammad Summair Raza, Usman Qamar.
Raza, Muhammad Summair., author.; Qamar, Usman., author.
2017
Q334-342
Available Online

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Title Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications / by Muhammad Summair Raza, Usman Qamar.
Author Raza, Muhammad Summair., author.
ISBN 9789811049651
9811049653
9789811049651
9789811049644
9811049645
DOI https://doi.org/10.1007/978-981-10-4965-1.
Published Singapore : Springer Singapore : Imprint: Springer, 2017.
Language English
Description 1 online resource (XIII, 194 p. 75 illus). : illustrations.
Item Number 10.1007/978-981-10-4965-1. doi
Call Number Q334-342
Dewey Decimal Classification 006.3
Summary This book provides a comprehensive introduction to Rough Set-based feature selection. It enables the reader to systematically study all topics of Rough Set Theory (RST) including the preliminaries, advanced concepts and feature selection using RST. In addition, the book is supplemented with an RST-based API library that can be used to implement several RST concepts and RST-based feature selection algorithms. Rough Set Theory, proposed in 1982 by Zdzislaw Pawlak, is an area in constant development. Focusing on the classification and analysis of imprecise or uncertain information and knowledge, it has become a prominent tool for data analysis. Feature selection is one of the important applications of RST, and helps us select the features that provide us with the largest amount of useful information. The book offers a valuable reference guide for all students, researchers, and developers working in the areas of feature selection, knowledge discovery and reasoning with uncertainty, especially those involved in RST and granular computing.
Access Note Access limited to authorized users.
Digital File Characteristics text file PDF
Added Author Qamar, Usman., author.
Available in Other Form Print version: 9789811049644
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Record Appears in Online Resources > Ebooks
All Resources
Introduction to Feature Selection
Background
Rough Set Theory
Advance Concepts in RST
Rough Set Based Feature Selection Techniques
Unsupervised Feature Selection using RST
Critical Analysis of Feature Selection Algorithms
RST Source Code.

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