A parallelized rule extraction method for high-dimensional pattern classification problems

Manabu Nii; Kousuke Ogino; Tomokazu Sakabe; Hitoshi Sakagami; Yutaka Takahashi

doi:10.11499/sicep.2002.0.159.0

SICE Annual Conference 2002

DOI https://doi.org/10.11499/sicep.2002.0.159.0

Conference information

Host: The Society of Instrument and Control Engineers

Co-host: IEEE/Industiral Electronic Society, IEEE/Robotics and Automation Society, IEEE/Control System Society

A parallelized rule extraction method for high-dimensional pattern classification problems

Manabu Nii, Kousuke Ogino, Tomokazu Sakabe, Hitoshi Sakagami, Yutaka Takahashi

Author information

Keywords: Rule extraction, neural networks, fuzzy if-then rules, parallel processing

CONFERENCE PROCEEDINGS FREE ACCESS

Pages 159

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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.

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