Abstract
In this study, we address the problem of finding the optimal number of clusters on incomplete data using cluster validity functions. Experiments were performed on different data sets in order to analyze to what extent cluster validity indices adapted to incomplete data can be used for validation of clustering results. Moreover we analyze which fuzzy clustering algorithm for incomplete data produces better partitioning results for cluster validity. © 2012 Springer-Verlag.
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Himmelspach, L., Carvalho, J. P., & Conrad, S. (2012). On cluster validity for fuzzy clustering of incomplete data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7520 LNAI, pp. 612–618). https://doi.org/10.1007/978-3-642-33362-0_50
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