AN IDEA OF SETTING WEIGHTING FUNCTIONS FOR FEATURE SELECTION

摘要：

　　In this paper,we propose a novel feature selection method,which improves effectively traditional mutual information based feature selection.The method takes as the first step traditional mutual information based feature selection.Then the method multiplies each feature by a weighting coefficient that is directly related to the mutual information value between the feature and class labels.Finally the multiplication results of the features with large mutual values are used as final features for classification.The result of nearest neighbor (NN) classification on spam emails filter and prediction of molecular bioactivity shows that the proposed method is able to improve the performance of NN classification.In additional,using fewer features NN classification is capable of achieving the same accuracy as NN classification using all of original features.

关键词： Pattern recognition Feature selection Nearest neighbor classification Mutual information Weighting coefficient

作者: Weijie Li Haiqiang Chen Wei Cao Xin Zhou

作者单位: China Information Technology Security Evaluation Center,Beijing 100085,China

会议类型: 国际会议

会议名称: 2012 2nd IEEE International Conference on Cloud Computing and Intelligence Systems (2012年第2届IEEE云计算与智能系统国际会议(IEEE CCIS2012))

会议地点: 杭州

会议语种:英文

页码: 909-914

在线出版日期: 2012-10-30（万方平台首次上网日期，不代表论文的发表时间）