Incomplete Information System and Rough Set Theory Models and Attribute Reductions /

"Incomplete Information System and Rough Set Theory: Models and Attribute Reductions" covers theoretical study of generalizations of rough set model in various incomplete information systems. It discusses not only the regular attributes but also the criteria in the incomplete information s...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Yang, Xibei (Autor), Yang, Jingyu (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2012.
Edición:1st ed. 2012.
Temas:
Data mining.
Computer science.
Artificial intelligence.
Database management.
Machine theory.
Data Mining and Knowledge Discovery.
Models of Computation.
Artificial Intelligence.
Database Management.
Formal Languages and Automata Theory.
Acceso en línea:Texto Completo
Descripción
Sumario:"Incomplete Information System and Rough Set Theory: Models and Attribute Reductions" covers theoretical study of generalizations of rough set model in various incomplete information systems. It discusses not only the regular attributes but also the criteria in the incomplete information systems. Based on different types of rough set models, the book presents the practical approaches to compute several reducts in terms of these models. The book is intended for researchers and postgraduate students in machine learning, data mining and knowledge discovery, especially for those who are working in rough set theory, and granular computing. Dr. Xibei Yang is a lecturer at the School of Computer Science and Engineering, Jiangsu University of Science and Technology, China; Jingyu Yang is a professor at the School of Computer Science, Nanjing University of Science and Technology, China.
Descripción Física:XIV, 232 p. online resource.
ISBN:9783642259357

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