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» Parameter Setting for Evolutionary Latent Class Clustering
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WEBI
2004
Springer
13 years 11 months ago
Mining Local Data Sources For Learning Global Cluster Models
— Distributed data mining has recently caught a lot of attention as there are many cases where pooling distributed data for mining is probibited, due to either huge data volume o...
Chak-Man Lam, Xiaofeng Zhang, William Kwok-Wai Che...
GECCO
2006
Springer
205views Optimization» more  GECCO 2006»
13 years 9 months ago
Bounding XCS's parameters for unbalanced datasets
This paper analyzes the behavior of the XCS classifier system on imbalanced datasets. We show that XCS with standard parameter settings is quite robust to considerable class imbal...
Albert Orriols-Puig, Ester Bernadó-Mansilla
GECCO
2010
Springer
197views Optimization» more  GECCO 2010»
13 years 9 months ago
Niching the CMA-ES via nearest-better clustering
We investigate how a niching based evolutionary algorithm fares on the BBOB function test set, knowing that most problems are not very well suited to this algorithm class. However...
Mike Preuss
PAMI
1998
128views more  PAMI 1998»
13 years 5 months ago
A Hierarchical Latent Variable Model for Data Visualization
—Visualization has proven to be a powerful and widely-applicable tool for the analysis and interpretation of multivariate data. Most visualization algorithms aim to find a projec...
Christopher M. Bishop, Michael E. Tipping
ICML
2009
IEEE
14 years 10 days ago
Fast evolutionary maximum margin clustering
The maximum margin clustering approach is a recently proposed extension of the concept of support vector machines to the clustering problem. Briefly stated, it aims at finding a...
Fabian Gieseke, Tapio Pahikkala, Oliver Kramer