A Bayesian Approach to Temporal Data Clustering using Hidden Markov Models
نویسندگان
چکیده
This paper presents clustering techniques that partition temporal data into homogeneous groups, and constructs state based proles for each group in the hidden Markov model (HMM) framework. We propose a Bayesian HMM clustering methodology that improves upon existing HMM clustering by incorporating HMM model size selection into clustering control structure to derive better cluster models and partitions. Experimental results indicate the e ectiveness of our methodology.
منابع مشابه
Computer Science a Bayesian Approach to Temporal Data Clustering Using the Hidden Markov Model Methodology
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