The use of positive and negative equivalence constraints in model-based clustering
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Date
Authors
Melnykov, V.
Melnykov, I.
Michael, S.
Journal Title
Journal ISSN
Volume Title
Publisher
Nazarbayev University
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.