The notion of defining a cluster as a component in a mixture model was put forth by
Tiedeman in 1955; since then, the use of mixture models for clustering has grown into an …

The majority of model-based clustering techniques is based on multivariate normal models
and their variants. In this paper copulas are used for the construction of flexible families of …

Time series clustering with a dissimilarity matrix based on tail dependence coefficients
estimated by copula functions has been proposed in 2011 by De Luca and Zuccolotto, who …

Copulas are distribution functions with standard uniform univariate marginals. Copulas are
widely used for studying dependence among continuously distributed random variables …

We review some recent clustering methods based on copulas. Specifically, in the
dissimilarity–based clustering framework, we describe and compare methods based on …

The random forest algorithm could be enhanced and produce better results with a well-
designed and organized feature selection phase. The dependency structure between the …

The aim of the paper is to explore the evolution of food diets in 40 European countries
according to the common European policies and guidelines on healthy diets. To this end, an …

In this work we are interested in identifying clusters of “positional equivalent” actors, ie actors
who play a similar role in a system. In particular, we analyze weighted bipartite networks that …

The objective of the paper is a contribution to data mining within the framework of the
observational calculus, through introducing ǵeneralized quantifiers related to copulas …

This paper deals with the problem of clustering dependent observations according to their
underlying complex generating process. Di Lascio and Giannerini (Journal of Classification …