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2019 | OriginalPaper | Buchkapitel

Clustering via Nonsymmetric Partition Distributions

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Abstract

Random partition models are widely used to perform clustering, since their features make them appealing options. However, additional information regarding group properties is not straightforward to incorporate under this approach. In order to overcome this difficulty, a novel approach to infer about clustering is presented. By relaxing the symmetry property of random partitions’ distributions, we are able to include group sizes in the computation of the probabilities. A Bayesian model is also given, together with a sampling scheme, and it is tested using simulated and real datasets.

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Metadaten
Titel
Clustering via Nonsymmetric Partition Distributions
verfasst von
Asael Fabian Martínez
Copyright-Jahr
2019
DOI
https://doi.org/10.1007/978-3-030-31551-1_6