Clustering mixed-type data via Dirichlet process mixture model with cluster-specific covariance matrices
Many studies have shown successful applications of the Dirichlet process mixture model (DPMM) for clustering continuous data. Beyond continuous data, in practice, one can expect to see different data types, including ordinal and nominal data. Existing DPMMs for clustering mixed-type data assume a st...
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Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
Multidisciplinary Digital Publishing Institute (MDPI)
2024
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Online Access: | http://psasir.upm.edu.my/id/eprint/113587/1/113587.pdf http://psasir.upm.edu.my/id/eprint/113587/ https://www.mdpi.com/2073-8994/16/6/712 |
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Institution: | Universiti Putra Malaysia |
Language: | English |
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