Using fuzzy dependency-guided attribute grouping in feature selection

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2639, Issue , 2003, Pages 250-254

  Jensen, Richard ^a   Shen, Qiang ^a  

^a UNIVERSITY OF EDINBURGH   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

FEATURE EXTRACTION; FUZZY SETS; GRANULAR COMPUTING; LEARNING SYSTEMS; ROUGH SET THEORY; CONSTRAINT THEORY; DATA MINING; NEURAL NETWORKS;

ATTRIBUTE REDUCTION; CLASSIFICATION ACCURACY; FUZZY DEPENDENCY; HIGH-DIMENSIONAL; INPUT FEATURES; LEARNING CLASSIFIERS; MACHINE LEARNING TECHNIQUES;

DATA MINING; ARTIFICIAL INTELLIGENCE;

EID: 8344241180     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-39205-x_32     Document Type: Conference Paper

References (6)

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4. R. Jensen and Q. Shen. Fuzzy-Rough Sets for Descriptive Dimensionality Reduction. Proceedings of the 11th International Conference on Fuzzy Systems, pp. 29-34, 2002.
5. Z. Pawlak. Rough Sets: Theoretical Aspects of Reasoning About Data. Kluwer Academic Publishing, Dordrecht, 1991.
6. Q. Shen and A. Chouchoulas. A modular approach to generating fuzzy rules with reduced attributes for the monitoring of complex systems. EAAI, 13(3):263-278, 2000.