Matrix computation for dynamic modification of rough set information system

Author

Tan, Tian-le ; Li, Ping ; Song, Zhi-huan

Author_Institution

Inst. of Ind. Process Control, Zhejiang Univ., Hangzhou, China

Volume

3

fYear

2003

fDate

2-5 Nov. 2003

Firstpage

1692

Abstract

For online learning of a rule-based knowledge system, algorithms for dynamic modification of rules are needed. This paper proposes strategies of rule updating in rough set information system. Based on the concept of equivalence matrix that expresses equivalence relation, matrix algorithms for induction and modification of decision rules are given. The relations between equivalence matrix and equivalence classes are discussed. Complexity analysis shows that these algorithms are efficient for rule adjusting and unnecessary computation can be avoided.

Keywords

computational complexity; decision theory; equivalence classes; information systems; knowledge based systems; learning (artificial intelligence); matrix algebra; rough set theory; complexity analysis; decision rules; equivalence classes; equivalence matrix; equivalence relation; matrix computation; online learning; rough set information system; rule updating; rule-based knowledge system; Algorithm design and analysis; Databases; Electrical equipment industry; Hardware; Heuristic algorithms; Industrial control; Information systems; Knowledge based systems; Process control; Set theory;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2003 International Conference on

Print_ISBN

0-7803-8131-9

Type

conf

DOI

10.1109/ICMLC.2003.1259769

Filename

1259769