Discretization Based Feature Selection for Support Vector Machines
Xiao‐Ming Xu · Jisuanji gongcheng · 2006
This paper presents a feature selection algorithm for support vector machine based on the rough sets and Boolean reasoning approach put forward by Nguyen.The level of consistency,coined from the rough sets theory,is introduced to measure the information loss during discretization so that irrelative or redundant attributes are eliminated while the necessary information for classification is preserved.Experiment results show that the presented algorithm can improve the prediction accuracy and reduce the training time of support vector machine.