Journal article
Minimum-entropy data partitioning using reversible jump Markov chain Monte Carlo
- Abstract:
-
Problems in data analysis often require the unsupervised partitioning of a data set into classes. Several methods exist for such partitioning but many have the weakness of being formulated via strict parametric models (e.g., each class is modeled by a single Gaussian) or being computationally intensive in high-dimensional data spaces. We reconsider the notion of such cluster analysis in information-theoretic terms and show that an efficient partitioning may be given via a minimization of part...
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- Publication status:
- Published
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- Publisher copy:
- 10.1109/34.946994
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Bibliographic Details
- Journal:
- IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Volume:
- 23
- Issue:
- 8
- Pages:
- 909-914
- Publication date:
- 2001-08-01
- DOI:
- ISSN:
-
0162-8828
- Source identifiers:
-
62949
Item Description
- Language:
- English
- Keywords:
- Pubs id:
-
pubs:62949
- UUID:
-
uuid:7c4188f0-8685-4b57-8f41-de4e0b8d768e
- Local pid:
- pubs:62949
- Deposit date:
- 2012-12-19
Terms of use
- Copyright date:
- 2001
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