郑州轻工业学院学报(自然科学版)2011，Vol.26Issue(2)：106-110,5.
基于线性判别分析和二分K均值的高维数据自适应聚类方法
Adaptive clustering method based on linear discriminant analysis and bisecting K-means for high dimensional data
摘要
Abstract
Combining linear discriminant analysis ( LDA ) and bisecting K-means clustering ( BKM ), an adaptively clustering method was proposed for high dimensional data.The method uses LDA to transform the high dimensional dataset into low dimensional one, applies BKM on the low dimensional dataset, and constructs the clusters in the original high dimensional dataset.The method is adaptively executed to generate the best result.Extensive experimental results on real-world datasets showed the effectiveness of the approach.关键词
维归约/线性判别分析/二分K均值/高维数据自适应聚类方法分类
信息技术与安全科学引用本文复制引用
汪万紫,裘国永,张兵权..基于线性判别分析和二分K均值的高维数据自适应聚类方法[J].郑州轻工业学院学报(自然科学版),2011,26(2):106-110,5.基金项目
陕西省自然科学基金项目(2010J M8039 ) （2010J M8039 ）
