Bayesian clustering by dynamics

Machine Learning

Volumn 47, Issue 1, 2002, Pages 91-121

  Ramoni, Marco ^a   Sebastiani, Paola ^b   Cohen, Paul ^c  

^a BOSTON CHILDREN S HOSPITAL   (United States)

^b UNIVERSITY OF MASSACHUSETTS   (United States)

^c Biologically Inspired Neural and Dynamical Systems Laboratory   (United States)

Author keywords

Bayesian learning; Clustering; Entropy; Heuristic search; Markov chains; Time series

Indexed keywords

DATA REDUCTION; HEURISTIC METHODS; MARKOV PROCESSES; MATHEMATICAL MODELS; MOBILE ROBOTS;

BAYESIAN CLUSTERING;

LEARNING SYSTEMS;

EID: 0036532775     PISSN: 08856125     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1013635829250     Document Type: Article

References (20)

1. Bayesian classification (AutoClass): Theory and results
2. A Bayesian method for the induction of probabilistic networks from data
3. Experiments in abstracting from robot sensor data using hidden markov models
4. A discriminative framework for detecting remote protein homologies
5. An invariant form for the prior probability in estimation procedures
6. Models of molecular evolution and phylogeny
7. Identifying distinctive subsequences in multivariate time series by clustering
8. Mixed Markov and latent Markov modelling applied to brand choice behavior
9. A tutorial on Hidden Markov Models and selected applications in speech recognition
10. Bayesian methods
11. Unsupervised clustering of robot activities: A Bayesian approach
12. Multivariate clustering by dynamics
13. Clustering finite discrete markov chains
14. Mixed memory markov models: Decomposing complex stochastic processes as mixture of simpler ones
15. Probabilistic model-based clustering of multivariate and sequential data
16. Probabilistic independence networks for hidden Markov probability models