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170703 ||| eng |
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|a 9789811049651
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| 100 |
1 |
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|a Raza, Muhammad Summair
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| 245 |
0 |
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|a Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications
|h Elektronische Ressource
|c by Muhammad Summair Raza, Usman Qamar
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| 250 |
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|a 1st ed. 2017
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| 260 |
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|a Singapore
|b Springer Nature Singapore
|c 2017, 2017
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| 300 |
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|a XIII, 194 p. 75 illus
|b online resource
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| 505 |
0 |
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|a 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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| 653 |
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|a Numerical Analysis
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| 653 |
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|a Artificial Intelligence
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| 653 |
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|a Data mining
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| 653 |
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|a Database Management
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| 653 |
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|a Application software
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| 653 |
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|a Artificial intelligence
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| 653 |
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|a Numerical analysis
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| 653 |
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|a Data Mining and Knowledge Discovery
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| 653 |
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|a Computer and Information Systems Applications
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| 653 |
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|a Database management
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| 700 |
1 |
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|a Qamar, Usman
|e [author]
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
|
| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-981-10-4965-1?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 006.3
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| 520 |
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|a 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
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