Improved Cluster Partition in Principal Component Analysis Guided Clustering

Abstract

Principal component analysis (PCA) guided clustering approach is widely used in high dimensional data to improve the efficiency of Kmeans cluster solutions. Typically, Pearson correlation is used in PCA to provide an eigenanalysis to obtain the associated components that account for most of the variations in the data. However, PCA based Pearson correlation… (More)

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