Co-Clustering with Generative Models
Name
MIT-CSAIL-TR-2009-054.pdf
Size
219.77 KB
Format
Adobe PDF
Checksum (MD5)
a485e99c6686d25a6d6d64ec51aa5036
Author(s)
Golland, Polina
Lashkari, Danial
Advisor(s)
Polina Golland
Date Issued
November 3, 2009
Series/Report no.
MIT-CSAIL-TR-2009-054
Abstract
In this paper, we present a generative model for co-clustering and develop algorithms based on the mean field approximation for the corresponding modeling problem. These algorithms can be viewed as generalizations of the traditional model-based clustering; they extend hard co-clustering algorithms such as Bregman co-clustering to include soft assignments. We show empirically that these model-based algorithms offer better performance than their hard-assignment counterparts, especially with increasing problem complexity.
Persistent DSpace Link
