Generalizing Centroid Index to Different Clustering Models
نویسندگان
چکیده
Centroid index is the only measure that evaluates cluster level differences between two clustering results. It outputs an integer value of how many clusters are differently allocated. In this paper, we apply this index to other clustering models that do not use centroid as prototype. We apply it to centroid model, Gaussian mixture model, and arbitrary-shape clusters.
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