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

抄録

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.