Model-Based Clustering — Discussion on Some Approaches

Abstract

One of the most well grounded approaches in clustering is model-based clustering, where one assumes particular multivariate distribution for each class. Most results in model-based clustering were obtained under multivariate normal distribution. In the paper we propose to adopt other approach, namely copula analysis in model-based clustering. Two possible stochastic approaches, namely classification approach and mixture approach, are considered as the framework to apply copula analysis. In the paper iterative algorithms are proposed to find optimal solution of clustering problem.