Chapter 5

HMM-Based Hybrid Meta-Clustering in Association With Ensemble Technique

Abstract

In the previous chapters, we had a comprehensive survey on background knowledge of this book including temporal data mining, temporal data clustering, and ensemble learning. Now, we are going to present a novel Hidden Markov Model–based ensemble clustering approach. Such approach is designed to solve the problems in finding the intrinsic number of clusters and model initialization sensitivity, which commonly existed in temporal clustering tasks.

Keywords

Hidden Markov Model; Model-based clustering; Model selection; Motion trajectory; Temporal data; Time series

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