Abstract
Figure 2.1 portrays cluster analysis. This field comprises three problems: tendency assessment, clustering and validation. Given an unlabeled data set, ① is there substructure in the data? This is clustering tendency — should you look for clusters at all? Very few methods — fuzzy or otherwise — address this problem. Panayirci and Dubes (1983), Smith and Jain (1984), Jain and Dubes (1988), Tukey (1977) and Everitt (1978) discuss statistical and informal graphical methods (visual displays) for deciding what — if any — substructure is in unlabeled data.
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Bezdek, J.C., Keller, J., Krisnapuram, R., Pal, N.R. (1999). Cluster Analysis for Object Data. In: Fuzzy Models and Algorithms for Pattern Recognition and Image Processing. The Handbooks of Fuzzy Sets Series, vol 4. Springer, Boston, MA. https://doi.org/10.1007/0-387-24579-0_2
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