Screen LibraryUnderstanding and using rough set based feature selection : concepts, techniques and applications /
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-b...
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| Main Authors: | |
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| Group Author: | |
| Published: |
Springer,
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| Publisher Address: | Singapore : |
| Publication Dates: | [2017] |
| Literature type: | Book |
| Language: | English |
| Subjects: | |
| 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 |
| Carrier Form: | xiii, 194 pages : illustrations, forms ; 24 cm |
| Bibliography: | Includes bibliographical references. |
| ISBN: |
9789811049644 (hardback) : 9811049645 (hardback) |
| Index Number: | QA248 |
| CLC: | O144 |
| Call Number: | O144/R278 |
| Contents: | 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. |