A PROBABILISTIC SELF-ORGANIZING MAP FOR BINARY DATA TOPOGRAPHIC CLUSTERING
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Publication:3629847
DOI10.1142/S1469026808002351zbMath1171.68671OpenAlexW2141247603MaRDI QIDQ3629847
Nicoleta Rogovschi, Mustapha Lebbah, Younès Bennani
Publication date: 2 June 2009
Published in: International Journal of Computational Intelligence and Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1142/s1469026808002351
Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10)
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Cites Work
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- Shared farthest neighbor approach to clustering of high dimensionality, low cardinality data
- Classification of run-length encoded binary data
- WEBSOM -- Self-organizing maps of document collections
- Self-organizing maps: Generalizations and new optimization techniques
- On the generative probability density model in the self-organizing map
- Speed-up for the expectation-maximization algorithm for clustering categorical data
- A unified view on clustering binary data
- A classification EM algorithm for clustering and two stochastic versions
- Clustering for binary data and mixture models—choice of the model
- A Bayesian Analysis of Self-Organizing Maps
- An iterative initial-points refinement algorithm for categorical data clustering
- Unsupervised learning by probabilistic latent semantic analysis