A Clustering Approach Using Weighted Similarity Majority Margins
نویسندگان
چکیده
We propose a meta-heuristic algorithm for clustering objects that are described on multiple incommensurable attributes defined on different scale types. We make use of a bipolar-valued dual similaritydissimilarity relation and perform the clustering process by first finding a set of cluster cores and then building a final partition by adding the objects left out to a core in a way which best fits the initial bipolar-valued similarity relation.
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