Ebook: Incomplete Information System and Rough Set Theory: Models and Attribute Reductions
Author: Xibei Yang Jingyu Yang (auth.)
- Tags: Data Mining and Knowledge Discovery, Models and Principles, Artificial Intelligence (incl. Robotics), Database Management, Mathematical Logic and Formal Languages
- Year: 2012
- Publisher: Springer-Verlag Berlin Heidelberg
- Edition: 1
- Language: English
- pdf
"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.
"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.
"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.
Content:
Front Matter....Pages i-xiv
Front Matter....Pages 1-1
Indiscernibility Relation, Rough Sets and Information System....Pages 3-42
Front Matter....Pages 43-43
Expansions of Rough Sets in Incomplete Information Systems....Pages 45-99
Neighborhood System and Rough Set in Incomplete Information System....Pages 101-130
Front Matter....Pages 131-131
Dominance-based Rough Sets in “*” Incomplete Information System....Pages 133-168
Dominance-based Rough Sets in “?” Incomplete Information System....Pages 169-192
Front Matter....Pages 193-193
Multigranulation Rough Sets in Incomplete Information System....Pages 195-222
Back Matter....Pages 223-232
"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.
Content:
Front Matter....Pages i-xiv
Front Matter....Pages 1-1
Indiscernibility Relation, Rough Sets and Information System....Pages 3-42
Front Matter....Pages 43-43
Expansions of Rough Sets in Incomplete Information Systems....Pages 45-99
Neighborhood System and Rough Set in Incomplete Information System....Pages 101-130
Front Matter....Pages 131-131
Dominance-based Rough Sets in “*” Incomplete Information System....Pages 133-168
Dominance-based Rough Sets in “?” Incomplete Information System....Pages 169-192
Front Matter....Pages 193-193
Multigranulation Rough Sets in Incomplete Information System....Pages 195-222
Back Matter....Pages 223-232
....