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Article
D-optimality criterion for weighting variables in K-means clustering
The aim of the study is how to achieve best K-means clustering structure so that k groups uncovered reveal more meaningful within-group coherence by assigning weights w1,…,wm to m clustering variables Z1,…,Zm. We...
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Article
Enhancing parallel coordinate plot
Effective visual representation of data sets with many continuous variables is not easy even with modern statistical graphic tools. Among them, the parallel coordinate plot (PCP) is especially popular these da...
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Chapter and Conference Paper
Setting the Number of Clusters in K-Means Clustering
K-means clustering is an efficient non-hierarchical clustering method, which became widely used in data mining. In applying the method, however, one needs to specify k,the number of clusters, a priori. In this sh...
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Chapter and Conference Paper
Canonical Discriminant Analysis of Multinomial Samples with Applications to Textual Data
We develop the canonical discriminant analysis of the G groups data consisting of n 1, …, n G multinomial samples within each group, on ...
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Chapter and Conference Paper
Research and Applications of Quantification Methods in East Asian Countries
Quantification methods were established by Chikio Hayashi and his colleagues in 1950’s and have been widely used in Japan as tools for analyzing qualitative data. Applications in Japan and Korea are briefly re...
