Tech Report A Variational HEM Algorithm for Clustering Hidden Markov Models

Autor:	Coviello, Emanuele, Chan, Antoni B., Lanckriet, Gert R. G.
Rok vydání:	2011
Předmět:	Computer Science - Artificial Intelligence Statistics - Machine Learning
Druh dokumentu:	Working Paper
Popis:	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. Comment: 13 pages, 1 figure
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1109.1032 Zobrazit plný text záznamu View this record from Arxiv