Bayesian Clustering by Dynamics

Abstract

This paper introduces a Bayesian method for clustering dynamic processes. The method models dynamics as Markov chains and then applies an agglomerative clustering procedure to discover the most probable set of clusters capturing different dynamics. To increase efficiency, the method uses an entropy-based heuristic search strategy. A controlled experiment… (More)
DOI: 10.1023/A:1013635829250

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Cite this paper

@article{Ramoni2002BayesianCB, title={Bayesian Clustering by Dynamics}, author={Marco Ramoni and Paola Sebastiani and Paul R. Cohen}, journal={Machine Learning}, year={2002}, volume={47}, pages={91-121} }