Title :
Feature Selection Via Fuzzy Clustering
Author :
Sun, Hao-jun ; Sun, Mei ; Mei, Zhen
Author_Institution :
Coll. of Math. & Comput. Sci., Hebei Univ., Baoding
Abstract :
This paper deals with feature selection for classification with wrapper framework. We develop a new algorithm for feature selection, based on a fuzzy clustering technique and an iterative process verifying classification accuracy. By monitoring discrepancy between two cluster systems, one derived with full features of the dataset, the other one with a subset of features, we are able to evaluate representation power of the subset of features with respect to the original feature set . Experimental results confirm efficiency of the proposed algorithm
Keywords :
feature extraction; fuzzy set theory; iterative methods; matrix algebra; pattern classification; pattern clustering; feature selection; fuzzy clustering technique; iterative process; pattern classification; wrapper framework; Cybernetics; Data mining; Educational institutions; Electronic mail; Machine learning; Manifolds; Mathematics; Sun; Fuzzy C-Means; classification error rate; clustering; feature selection;
Conference_Titel :
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location :
Dalian, China
Print_ISBN :
1-4244-0061-9
DOI :
10.1109/ICMLC.2006.258712
