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» Kernel MDL to Determine the Number of Clusters
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MLDM
2007
Springer
13 years 11 months ago
Kernel MDL to Determine the Number of Clusters
In this paper we propose a new criterion, based on Minimum Description Length (MDL), to estimate an optimal number of clusters. This criterion, called Kernel MDL (KMDL), is particu...
Ivan O. Kyrgyzov, Olexiy O. Kyrgyzov, Henri Ma&ici...
KDD
2006
ACM
173views Data Mining» more  KDD 2006»
14 years 5 months ago
Robust information-theoretic clustering
How do we find a natural clustering of a real world point set, which contains an unknown number of clusters with different shapes, and which may be contaminated by noise? Most clu...
Christian Böhm, Christos Faloutsos, Claudia P...
PAKDD
2005
ACM
142views Data Mining» more  PAKDD 2005»
13 years 10 months ago
Dynamic Cluster Formation Using Level Set Methods
Density-based clustering has the advantages for (i) allowing arbitrary shape of cluster and (ii) not requiring the number of clusters as input. However, when clusters touch each o...
Andy M. Yip, Chris H. Q. Ding, Tony F. Chan
ITSL
2008
13 years 6 months ago
An Empirical Comparison of NML Clustering Algorithms
Clustering can be defined as a data assignment problem where the goal is to partition the data into nonhierarchical groups of items. In our previous work, we suggested an informati...
Petri Kontkanen, Petri Myllymäki
CVPR
2011
IEEE
12 years 8 months ago
Max-margin Clustering: Detecting Margins from Projections of Points on Lines
Given a unlabelled set of points X ∈ RN belonging to k groups, we propose a method to identify cluster assignments that provides maximum separating margin among the clusters. We...
Raghuraman Gopalan, Jagan Sankaranarayanan