Quantitative Performance Analysis for the Family of Enhanced Strange Points Clustering Algorithms
نویسنده
چکیده
A cluster is expected to contain all elements that are of one kind and every element is supposed to be different from the elements of any other cluster. Any clustering algorithm which ensures the above is believed to output quality clusters. This paper gives a quantitative performance analysis for the family of enhanced strange points clustering algorithms and indicates how each algorithm in the family outputs a high quality of clustering results comparable to that of well-established clustering algorithms.
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