Topics in component merging in model-based clustering
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Model-based clustering models heterogeneous populations within a data set, where each component is often viewed as a cluster. However, the number of components may not always match that of the underlying clusters. In the case of over-estimation, merging some mixture components could help with identifying more informative clusters. In light of this issue, we will discuss some topics related to component merging in model-based clustering.