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The Block Generative Topographic Mapping
- Source :
- Artificial Neural Networks in Pattern Recognition ISBN: 9783540699385, ANNPR
- Publication Year :
- 2008
- Publisher :
- HAL CCSD, 2008.
-
Abstract
- This paper presents a generative model and its estimation allowing to visualize binary data. Our approach is based on the Bernoulli block mixture model and the probabilistic self-organizing maps. This leads to an efficient variant of Generative Topographic Mapping. The obtained method is parsimonious and relevant on real data.
- Subjects :
- Computer science
business.industry
Probabilistic logic
Pattern recognition
Mixture model
[STAT] Statistics [stat]
Generative model
Bernoulli's principle
Generative topographic map
Binary data
Artificial intelligence
Latent variable model
business
ComputingMilieux_MISCELLANEOUS
Block (data storage)
Subjects
Details
- Language :
- English
- ISBN :
- 978-3-540-69938-5
- ISBNs :
- 9783540699385
- Database :
- OpenAIRE
- Journal :
- Artificial Neural Networks in Pattern Recognition ISBN: 9783540699385, ANNPR
- Accession number :
- edsair.doi.dedup.....e288dad65244b0ce9b4f5a8f3b41b6e2