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CPS1950 Paolo G. et al.
References
1. Arabie, P. & Hubert, L. (1994). Cluster analysis in marketing research. In:
Bagozzi, R.P. (Ed.), Handbook of marketing research. Blackwell, Oxford.
2. Bezdek, J. C. (1981). Pattern Recognition with Fuzzy Objective Function
Algorithm. New York. Plenum Press.
3. Caliński, T. & Harabasz, J. (1974). A dendrite method for cluster analysis.
Comm. Statist., 3, 1–27. R.J.G.B. Campello, R. J. G. B. & Hruschka, E. R.
(2006). A fuzzy extension of the silhouette width criterion for cluster
analysis. Fuzzy Sets Syst., 157, 2858–2875.
4. Cutler, A. & Breiman, L. (1994) Archetypal analysis. Technometrics, 36,
338–347.
5. DeSarbo, W. S., Jedidi, K., Cool, K. & Schendel, D. (1990). Simultaneous
multidimensional unfolding and cluster analysis: an investigation of
strategic groups. Marketing Lett., 2, 129–146.
6. De Soete, G. & Carroll, J. D. (1994). k-means clustering in a low-
dimensional Euclidean space. In: Diday, E., et al. (Eds.), New Approaches
in Classification and Data Analysis. Springer, Heidelberg, pp.212–219.
7. Epifanio, I., Ibáñez, M. V. & Simó, A. (2018). Archetypal shapes based on
landmarks and extension to handle missing data. Adv. Data Anal. Classif.,
12, 705–735.
8. Ferraro, M. B., Giordani, P. & Serafini, A. (2018). fclust: an R package for
fuzzy clustering. Submitted.
9. Kaiser, H. F. (1958). The varimax criterion for analytic rotation in factor
analysis. Psychometrika, 23, 187–200.
10. Kaufman, L. & Rousseeuw, P. J. (1990). Finding Groups in Data: An
Introduction to Cluster Analysis. New York. Wiley.
11. MacQueen, J. (1967). Some methods for classification and analysis of
multivariate observations. Proc. Fifth Berkeley Symp. on Math. Statist.
and Prob., Vol. 1, Univ. of Calif. Press, 281-297.
12. Suleman, A. (2015). A convex semi-nonnegative matrix factorisation
approach to fuzzy c-means clustering. Fuzzy Sets Syst, 270, 90–110.
13. Timmerman, M. E., Ceulemans, E., Kiers, H. A. L. & Vichi, M. (2010).
Factorial and reduced K-means reconsidered. Comput. Statist. Data
Anal., 54, 1858–1871.
14. Vichi, M. & Kiers, H.A.L. (2001). Factorial k-means analysis for two-way
data. Comput. Statist. Data Anal., 37, 49-64.
15. Xie, X. L. & Beni, G. (1991). A validity measure for fuzzy clustering. IEEE
Trans. Pattern Anal. Mach. Intell., 13, 841–847.
16. Zadeh, L. A. (1965). Fuzzy sets. Inf. Control, 8, 338–353.

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