Design of Hierarchical Fuzzy Classification System Based on Statistical Characteristics of Data

Chang Sik SON  Yoon-Nyun KIM  Kyung-Ri PARK  Hee-Joon PARK  

IEICE TRANSACTIONS on Information and Systems   Vol.E93-D    No.8    pp.2319-2323
Publication Date: 2010/08/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E93.D.2319
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Pattern Recognition
hierarchical fuzzy classification system,  fuzzy partitioning,  rule generation,  

Full Text: PDF(722.2KB)>>
Buy this Article

A scheme for designing a hierarchical fuzzy classification system with a different number of fuzzy partitions based on statistical characteristics of the data is proposed. To minimize the number of misclassified patterns in intermediate layers, a method of fuzzy partitioning from the defuzzified outputs of previous layers is also presented. The effectiveness of the proposed scheme is demonstrated by comparing the results from five datasets in the UCI Machine Learning Repository.

open access publishing via