FUZZY PARTITIONING OF FEATURE SPACE FOR PATTERN CLASSIFICATION BASED ON SUPERVISED ClUSTERING

摘要

The choice of a fuzzy partitioning is crucial to the performance of a fuzzy system based on if then rules. However, most of the existing methods are complicated or lead to too many subspaces, which is unfit for the applications of pattern classification. A simple but ef fective clustering approach is proposed in this paper, which obtains a set of compact subspaces and is applicable for classification problems with higher dimensional feature. Its effectiveness is demonstrated by the experimental results.