Study on PCA based Hierarchical k-means Clustering Algorithm

The traditional H-K clustering algorithms combined the hierarchical clustering algorithm and the k-means clustering algorithm,made H-K clustering algorithm have many merits which a single clustering algorithm doesn't achieve.In order to make H-K clustering algorithms applied better in the Clustering of high-dimensional data sets and alleviate dimension disaster problem,in this paper,it is applied PCA method to H-K clustering algorithm for improvement,and proposed a new algorithm which we named as PCAHK.The algorithm firstly adopts PCA method to project high dimensional data into the lower dimensional space,then executes H-K clustering on the low dimensional data sets.The experiments show that the PCAHK algorithm get better performance than the traditional H-K clustering algorithm for the clustering of high-dimensional data sets.