PROBABILISTIC DISTANCE CLUSTERING ADJUSTED FOR CLUSTER SIZE

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Date

2008-01-01

Author

İyigün, Cem
BEN-ISRAEL, Adi

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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.

Subject Keywords

Management Science and Operations Research, Statistics, Probability and Uncertainty, Statistics and Probability, Industrial and Manufacturing Engineering

URI

https://hdl.handle.net/11511/38932

Journal

PROBABILITY IN THE ENGINEERING AND INFORMATIONAL SCIENCES

DOI

https://doi.org/10.1017/s0269964808000351

Collections

Department of Industrial Engineering, Article

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.