TY - GEN
T1 - Multiplicative mixture models for overlapping clustering
AU - Qiang, Fu
AU - Banerjee, Arindam
PY - 2008
Y1 - 2008
N2 - The problem of overlapping clustering, where a point is allowed to belong to multiple clusters, is becoming increasingly important in a variety of applications. In this paper, we present an overlapping clustering algorithm based on multiplicative mixture models. We analyze a general setting where each component of the multiplicative mixture is from an exponential family, and present an efficient alternating maximization algorithm to learn the model and infer overlapping clusters. We also show that when each component is assumed to be a Gaussian, we can apply the kernel trick leading to non-linear cluster separators and obtain better clustering quality. The efficacy of the proposed algorithms is demonstrated using experiments on both UCI enchmark datasets and a microarray gene expression dataset.
AB - The problem of overlapping clustering, where a point is allowed to belong to multiple clusters, is becoming increasingly important in a variety of applications. In this paper, we present an overlapping clustering algorithm based on multiplicative mixture models. We analyze a general setting where each component of the multiplicative mixture is from an exponential family, and present an efficient alternating maximization algorithm to learn the model and infer overlapping clusters. We also show that when each component is assumed to be a Gaussian, we can apply the kernel trick leading to non-linear cluster separators and obtain better clustering quality. The efficacy of the proposed algorithms is demonstrated using experiments on both UCI enchmark datasets and a microarray gene expression dataset.
UR - http://www.scopus.com/inward/record.url?scp=67049165529&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=67049165529&partnerID=8YFLogxK
U2 - 10.1109/ICDM.2008.103
DO - 10.1109/ICDM.2008.103
M3 - Conference contribution
AN - SCOPUS:67049165529
SN - 9780769535029
T3 - Proceedings - IEEE International Conference on Data Mining, ICDM
SP - 791
EP - 796
BT - Proceedings - 8th IEEE International Conference on Data Mining, ICDM 2008
T2 - 8th IEEE International Conference on Data Mining, ICDM 2008
Y2 - 15 December 2008 through 19 December 2008
ER -