DocumentCode
393465
Title
A parallelized rule extraction method for high-dimensional pattern classification problems
Author
Nii, Manabu ; Ogino, Kousuke ; Sakabe, Tomokazu ; Sakagami, Hitoshi ; Takahashi, Yutaka
Author_Institution
Div. of Comput. Eng., Himeji Inst. of Technol., Hyogo, Japan
Volume
2
fYear
2002
fDate
5-7 Aug. 2002
Firstpage
740
Abstract
In this paper, we propose a parallelized rule extraction method from trained neural networks for high-dimensional pattern classification problems. In the rule extraction method, we have to examine all combinations of antecedent fuzzy sets for extracting fuzzy rules. For high-dimensional problems, the number of possible combinations is increased exponentially. To address this difficulty, we parallelize the rule extraction method.
Keywords
learning (artificial intelligence); neural nets; pattern classification; antecedent fuzzy sets; fuzzy if-then rules; parallelized rule extraction method; pattern classification; rule extraction; trained neural networks; Computer networks; Concurrent computing; Feedforward neural networks; Fuzzy neural networks; Fuzzy sets; Microcomputers; Multi-layer neural network; Neural networks; Parallel processing; Pattern classification;
fLanguage
English
Publisher
ieee
Conference_Titel
SICE 2002. Proceedings of the 41st SICE Annual Conference
Print_ISBN
0-7803-7631-5
Type
conf
DOI
10.1109/SICE.2002.1195248
Filename
1195248
Link To Document