Cluster validation in k-Means clustering of mixed databases based on principal component analysis
作者： Ryoichi Nonoguchi , Katsuhiro Honda , Akira Notsu , Hidetomo Ichihashi
DOI: 10.1109/SCIS-ISIS.2012.6505102
关键词: Database 、 Artificial intelligence 、 k-medians clustering 、 Computer science 、 Rotation (mathematics) 、 Cluster analysis 、 Single-linkage clustering 、 Relation (database) 、 Data mining 、 Categorical variable 、 k-means clustering 、 Principal component analysis 、 Pattern recognition
摘要: Considering the close relation between k-Means clustering and principal component analysis (PCA), a cluster validation approach for partitions was proposed using analytical solutions of PCA. In this paper, is further extended handling mixed databases composed not only numerical observations but also categorical observations. new databases, PCA are given by considering optimal scaling category observations, plausibility evaluated calculating deviations from after Procrustean rotation.
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