PROBABILISTIC DISTANCE CLUSTERING ADJUSTED FOR CLUSTER SIZE

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2008-01-01
İyigün, Cem
BEN-ISRAEL, Adi
The probabilistic distance clustering method of [1] works well if the cluster sizes are approximately equal. We modify that method to deal with clusters of arbitrary size and for problems where the cluster sizes are themselves unknowns that need to be estimated. In the latter case, our method is a viable alternative to the expectation-maximization (EM) method.

Citation Formats
C. İyigün and A. BEN-ISRAEL, “PROBABILISTIC DISTANCE CLUSTERING ADJUSTED FOR CLUSTER SIZE,” PROBABILITY IN THE ENGINEERING AND INFORMATIONAL SCIENCES, vol. 22, no. 4, pp. 603–621, 2008, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/38932.