A novel Text Classification Based on Mahalanobis distance

摘要：

In text mining Held, The KNN (K Nearest Neighbors) is one of the oldest and simplest methods of text classification. But it is known to be sensitive to the distance (or similarity) function used in classifying a test instance, this disadvantage can cause low classification accuracy and limit the KNN classifiers utilization in text classification in text mining. In this paper, we introduce Mahalanobis distance in text classification area, and proposed an algorithm (MDKNN) base on this theory. Experiment show that our method has comparable or better performance than KNN Classifier and Naive Bayes classifier in text classification.

关键词： Mahalanobis distance KNN Classifier Text Classification Chinese

作者: Suli Zhang Xin Pan

作者单位: School of Electrical & Information Technology Changchun Institute of Technology Changchun,China

会议类型: 国际会议

会议名称: 2011 3rd IEEE International Conference on Computer Research and Development(ICCRD 2011)(2011第三届计算机研究与发展国际会议)

会议地点: 上海

会议语种:英文

页码: 156-158

在线出版日期: 2011-03-11（万方平台首次上网日期，不代表论文的发表时间）