Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques

Description: Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications by Muhammad Summair Raza, Usman Qamar Estimated delivery 3-12 business days Format Paperback Condition Brand New Description This book provides a comprehensive introduction to rough set-based feature selection. The dominance-based rough set approach (DRSA) is an extension of the conventional rough set approach and supports the preference order using the dominance principle. Publisher Description This book provides a comprehensive introduction to rough set-based feature selection. Rough set theory, first proposed by Zdzislaw Pawlak in 1982, continues to evolve. Concerned with the classification and analysis of imprecise or uncertain information and knowledge, it has become a prominent tool for data analysis, and enables the reader to systematically study all topics in rough set theory (RST) including preliminaries, advanced concepts, and feature selection using RST. 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.The book provides an essential reference guide for students, researchers, and developers working in the areas of feature selection, knowledge discovery, and reasoning with uncertainty, especially those who are working in RST and granular computing. The primary audience of this book is the research community using rough set theory (RST) to perform feature selection (FS) on large-scale datasets in various domains. However, any community interested in feature selection such as medical, banking, and finance can also benefit from the book. This second edition also covers the dominance-based rough set approach and fuzzy rough sets. The dominance-based rough set approach (DRSA) is an extension of the conventional rough set approach and supports the preference order using the dominance principle. In turn, fuzzy rough sets are fuzzy generalizations of rough sets. An API library for the DRSA is also provided with the second edition of the book. Author Biography Dr. Muhammad Summair Raza holds a Ph.D. specialization in Software Engineering from the National University of Science and Technology (NUST), Pakistan. He completed his M.S. at the International Islamic University, Pakistan, in 2009. He is also associated with the Virtual University of Pakistan as an Assistant Professor. Having published various papers in international-level journals and conference proceedings, his research interests include Feature Selection, Rough Set Theory and Trend Analysis. Dr. Usman Qamar has over 15 years of experience in data engineering in both academia and industry. He holds a Masters in Computer Systems Design from the University of Manchester Institute of Science and Technology (UMIST), UK, as well as an M.Phil. and Ph.D. in Computer Science from the University of Manchester, UK. Dr Qamars research expertise is in Data and Text Mining, Expert Systems, Knowledge Discovery, and Feature Selection, areas in which he has published extensively. He is currently a Tenured Associate Professor at the Department of Computer & Software Engineering, National University of Sciences and Technology (NUST), Pakistan, where he also heads the Knowledge and Data Engineering Research Centre (KDRC). Details ISBN 9813291680 ISBN-13 9789813291683 Title Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications Author Muhammad Summair Raza, Usman Qamar Format Paperback Year 2020 Pages 236 Edition 2nd Publisher Springer Verlag, Singapore GE_Item_ID:140451747; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. 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