Improved K-Modes for Categorical Clustering Using Weighted Dissimilarity Measure

@inproceedings{Aranganayagi2009ImprovedKF,
  title={Improved K-Modes for Categorical Clustering Using Weighted Dissimilarity Measure},
  author={S. Aranganayagi and Kalaivani Thangavel},
  year={2009}
}
K-Modes is an extension of K-Means clustering algorithm, developed to cluster the categorical data, where the mean is replaced by the mode. The similarity measure proposed by Huang is the simple matching or mismatching measure. Weight of attribute values contribute much in clustering; thus in this paper we propose a new weighted dissimilarity measure for K-Modes, based on the ratio of frequency of attribute values in the cluster and in the data set. The new weighted measure is experimented with… CONTINUE READING
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