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Temporal Pattern Generation Using Hidden Markov Model Based Unsupervised Classification

IDA, (1999): 245-256

Cited by: 66|Views7
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Abstract

This paper describes a clustering methodology for temporal data using hidden Markov model(HMM) representation. The proposed method improves upon existing HMM based clustering methods in two ways: (i) it enables HMMs to dynamically change its model structure to obtain a better fit model for data during clustering process, and (ii) it provi...More

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