Dissimilarity Measures

This exploratory work aims to avoid this premature integration of attribute types prior to cluster analysis through a multi-objective evolutionary algorithm called MVMC.

We investigate the interaction between the clustering criteria employed in a multi-objective algorithm and the distance functions on which these criteria operate.

Here we describe the design of an evolutionary algorithm for the problem of multi-view data clustering. The use of a many-objective evolutionary algorithm addresses limitations of previous work, as the resulting method should be capable of scaling to settings with four or more views.