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Abstract: Reliable clustering of a severely contaminated data must depend on robust estimation methods to determine the cluster prototypes. The Least Median of Squares (LMedS) can estimate the parameters of a single prototype with a 50% breakdown point. However this breakdown point cannot be achieved when a data set consists of multiple clusters. In addition to this limitation, the objective function of the LMedS is neither amenable to analytical optimization nor to numerical optimization because of its... (Update)
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BibTeX entry: (Update)
O. Nasraoui and R. Krishnapuram, "Clustering using a genetic fuzzy least median of squares algorithm," in North American Fuzzy Information Processing Society Conference, (Syracuse NY), Sep. 1997. http://citeseer.ist.psu.edu/nasraoui97clustering.html More
@misc{ nasraoui97clustering,
author = "O. Nasraoui and R. Krishnapuram",
title = "Clustering using a genetic fuzzy least median of squares algorithm",
text = "O. Nasraoui and R. Krishnapuram, Clustering using a genetic fuzzy least
median of squares algorithm, in North American Fuzzy Information Processing
Society Conference, (Syracuse NY), Sep. 1997.",
year = "1997",
url = "citeseer.ist.psu.edu/nasraoui97clustering.html" }
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