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SCHOLARPEDIA
2008
89views more  SCHOLARPEDIA 2008»
13 years 6 months ago
Support vector clustering
We present a novel method for clustering using the support vector machine approach. Data points are mapped to a high dimensional feature space, where support vectors are used to d...
Asa Ben-Hur
ISICA
2007
Springer
14 years 2 months ago
Parameter Setting for Evolutionary Latent Class Clustering
The latent class model or multivariate multinomial mixture is a powerful model for clustering discrete data. This model is expected to be useful to represent non-homogeneous popula...
Damien Tessier, Marc Schoenauer, Christophe Bierna...
KDD
2009
ACM
181views Data Mining» more  KDD 2009»
14 years 3 months ago
An exploration of climate data using complex networks
To discover patterns in historical data, climate scientists have applied various clustering methods with the goal of identifying regions that share some common climatological beha...
Karsten Steinhaeuser, Nitesh V. Chawla, Auroop R. ...
SDM
2008
SIAM
177views Data Mining» more  SDM 2008»
13 years 9 months ago
Robust Clustering in Arbitrarily Oriented Subspaces
In this paper, we propose an efficient and effective method to find arbitrarily oriented subspace clusters by mapping the data space to a parameter space defining the set of possi...
Elke Achtert, Christian Böhm, Jörn David...
ISAAC
2004
Springer
121views Algorithms» more  ISAAC 2004»
14 years 1 months ago
Approximate Distance Oracles for Graphs with Dense Clusters
Let G be a graph containing N disjoint t-spanners that are inter-connected with M edges. We present an algorithm that constructs a data structure of size O(M2 + n log n) that answ...
Mattias Andersson, Joachim Gudmundsson, Christos L...