The use of positive and negative equivalence constraints in model-based clustering

Abstract

Cluster analysis is a popular technique in statistics and computer science with the objective to group similar observations into relatively distinct groups known as clusters. Semi-supervised model-based clustering assumes that some additional information about group memberships is available.