Fuzzy c-means clustering of incomplete data

By Richard J. Hathaway, James C. Bezdek. IEEE Trans. Syst. Man Cybern. Part B, 2001

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Pattern classification with missing data: a review (2010, methodology): “Other fuzzy solutions for missing values are based on fuzzy C-means [74–76].”
Some Notes on Alternating Optimization (2002, methodology): “We list a very few examples of alternating optimization that appear in the clustering and mixture decomposition literature: hard c-means [1]; the expectationmaximization algorithm for estimating the parameters in a mixture of normal distributions [2]; fuzzy c-means [3]; fuzzy c- varieties [4]; assig”
Survey of clustering algorithms (2005, methodology): “Chameleon [159] is a newly developed agglomerative HC algorithm based on the -nearest-neighbor graph, in which an edge is eliminated if both vertices are not within the closest points related to each other.”