Mode merging for non-Gaussian Finite Mixtures
Date:
Finite mixture models can be interpreted as a model representing heterogeneous sub-populations within the whole population. However, more care is needed when associating a mixture component with a cluster, because a mixture model may fit more components than the number of clusters. Modal merging via the mean shift algorithm can help identifysuch multi-component clusters. So far, most of the related works are focused on the Gaussian finite mixture. As the non-Gaussian finite mixtures gain attention, the need to address the component-cluster correspondence issue in these mixture models grows. In light of this issue, we introduce mode merging methods for several non-Gaussian finite mixtures including power-exponential, normal variance mixture and normal variance-mean mixture.