Clustering validity checking methods: Part II
Clustering results validation is an important topic in the context of pattern recognition. We review approaches and systems in this context. In the first part of this paper we presented clustering validity checking approaches based on internal and external criteria. In the second, current part, we present a review of clustering validity approaches based on relative criteria. Also we discuss the results of an experimental study based on widely known validity indices. Finally the paper illustrates the issues that are under-addressed by the recent approaches and proposes the research directions in the field.
clustering validation pattern discovery unsupervised learning