Encyclopedia of Statistics in Behavioral Science Everitt Behavioral
Fuzzy Cluster Analysis
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Manton, KG; Lowrimore, G; Yashin, A; Kovtun, M
January 1, 2006
Usually in cluster analysis, an object is a member of one and only one cluster, a property described as ‘crisp’ membership. Fuzzy cluster analysis allows an object to have partial membership in more than one cluster. Selecting a good membership function is important to the success of the methods. The Grade of Membership model – which has a long history of usage in other contexts – is proposed as a straightforward way of performing fuzzy cluster analysis. The Grade of Membership model is illustrated by an example involving gene expression data.
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Manton, K. G., Lowrimore, G., Yashin, A., & Kovtun, M. (2006). Fuzzy Cluster Analysis. In Encyclopedia of Statistics in Behavioral Science Everitt Behavioral (pp. 1–10). https://doi.org/10.1002/0470013192.bsa240
Manton, K. G., G. Lowrimore, A. Yashin, and M. Kovtun. “Fuzzy Cluster Analysis.” In Encyclopedia of Statistics in Behavioral Science Everitt Behavioral, 1–10, 2006. https://doi.org/10.1002/0470013192.bsa240.
Manton KG, Lowrimore G, Yashin A, Kovtun M. Fuzzy Cluster Analysis. In: Encyclopedia of Statistics in Behavioral Science Everitt Behavioral. 2006. p. 1–10.
Manton, K. G., et al. “Fuzzy Cluster Analysis.” Encyclopedia of Statistics in Behavioral Science Everitt Behavioral, 2006, pp. 1–10. Scopus, doi:10.1002/0470013192.bsa240.
Manton KG, Lowrimore G, Yashin A, Kovtun M. Fuzzy Cluster Analysis. Encyclopedia of Statistics in Behavioral Science Everitt Behavioral. 2006. p. 1–10.