Feature selection based on information granularity and large margin
Daren Yu · Journal of Chongqing University of Posts and Telecommunications · 2010
Feature selection is used to find an optimal subset to reduce computational cost,increase classification accuracy and improve result comprehensibility.In this paper,we introduced a feature selection technique based on information granularity and large margin.Firstly,we operated the information granularity on raw data,and then based on information granularity we proposed fuzzy margin and class margin as the feature evaluation functions.The effectiveness of the proposed method was validated by experiments on different data sets.Experimental results show that the proposed technique has better performance than the other margin based feature selection methods.