Semi-supervised Classification Algorithm Based on the KNN

摘要：

KNN algorithm is a classification algorithm based on examples. For a test documentation, we need to calculate the similarity with each text of the training sample focus, the computation complexity is very high. According to this problem, this paper puts forward a method based on the EM -KNN semi-supervised classification algorithm. Firstly, the algorithm to cluster the training set, calculate the center of each category, then combine the center of each category and the clustering the text to form new training set. Finally train the new training set with classical KNN algorithm. Experimental results show that computational complexity can be reduced largely and the performance of the classifier can be improved by this algorithm.

关键词： Semi-supervised EM KNN Classification Clustering

作者: Yawei Chang Houquan Liu

作者单位: School of Computer Science and Technology China University of Mining & Technology Xuzhou,China

会议类型: 国际会议

会议名称: 2011 2nd International Conference on Data Storage and Data Engineering(DSDE 2011)(2011年第二届数据存储与数据工程国际会议)

会议地点: 西安

会议语种:英文

页码: 9-12

在线出版日期: 2011-05-13（万方平台首次上网日期，不代表论文的发表时间）