Raza Muhammad Summair, Qamar Usman Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications 9789813291652

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Автор: Raza Muhammad Summair, Qamar Usman
Название: Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications
ISBN: 9789813291652
Издательство: Springer
Классификация:

Вычислительная математика

Информационные технологии: общие вопросы

Базы данных

Извлечение знаний из данных

Искусственный интеллект

Экспертные системы / системы баз знаний

ISBN-10: 9813291656
Обложка/Формат: Hardcover
Страницы: 236
Вес: 0.53 кг.
Дата издания: 04.09.2019
Язык: English
Издание: 2nd ed. 2019
Иллюстрации: 27 illustrations, color; 120 illustrations, black and white; xvi, 236 p. 147 illus., 27 illus. in color.
Размер: 234 x 156 x 16
Читательская аудитория: Professional & vocational
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Германии
Описание: 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.
Дополнительное описание: Introduction to Feature Selection.- Background.- Rough Set Theory.- Advance Concepts in Rough Set Theory.- Rough Set Theory Based Feature Selection Techniques.- Chapter 6: Unsupervised Feature Selection using RST.- Critical Analysis of Feature Selection A

Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications, Raza Muhammad Summair, Qamar Usman