Abstract
This paper proposes a simultaneous application of homogeneity analysis and fuzzy clustering which simultaneously partitions individuals and items in categorical multivariate data sets. Taking the similarity between the loss of homogeneity in homogeneity analysis and the least squares criterion in principal component analysis into account, the new objective function is defined in a similar formulation to the linear fuzzy clustering. © Springer-Verlag Berlin Heidelberg 2005.
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CITATION STYLE
Oh, C. H., Honda, K., & Ichihashi, H. (2005). Quantification of multivariate categorical data considering clusters of items and individuals. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3558 LNAI, pp. 164–171). Springer Verlag. https://doi.org/10.1007/11526018_17
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