Adaptive clustering method based on linear discriminant analysis and bisecting K-means for high dimensional data

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.