Fuzzy Clustering Coefficient Variation

Fuzzy clustering variation looks for a good subset of attributes in order to improve the classification accuracy of supervised learning techniques in classification problems with a huge number of attributes involved. It first creates a ranking of attributes based on the Variation value, then divide into two groups, last using Verification method to select the best group.Simon Fong, Justin Liang, YanZhuang, "Improving Classification Accuracy Using Fuzzy Clustering Coefficients of Variations (FCCV) Feature Selection Algorithm", 2014 IEEE 15th International Symposium on Computational Intelligence and Informatics (CINTI), pp.147-151