Tech Report A Variational HEM Algorithm for Clustering Hidden Markov Models

Details Tech Report A Variational HEM Algorithm for Clustering Hidden Markov Models Tech Report A Variational HEM Algorithm for Clustering Hidden Markov Models

2011-09-06

arxiv.org/abs/1109.1032v1

Computer Science

Artificial Intelligence

13 pages, 1 figure

Scientific paper

The hidden Markov model (HMM) is a generative model that treats sequential data under the assumption that each observation is conditioned on the state of a discrete hidden variable that evolves in time as a Markov chain. In this paper, we derive a novel algorithm to cluster HMMs through their probability distributions. We propose a hierarchical EM algorithm that i) clusters a given collection of HMMs into groups of HMMs that are similar, in terms of the distributions they represent, and ii) characterizes each group by a "cluster center", i.e., a novel HMM that is representative for the group. We present several empirical studies that illustrate the benefits of the proposed algorithm.

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