A Family of Metrics for Clustering Algorithms
We give the motivation for scoring clustering algorithms and a metric M : A →N from the set of clustering algorithms to the natural numbers which we realize as M(A) = ∑_i α_i |f_i - β_i|^w_i where α_i,β_i,w_i are parameters used for scoring the feature f_i, which is computed empirically.. We give a method by which one can score features such as stability, noise sensitivity, etc and derive the necessary parameters. We conclude by giving a sample set of scores.
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