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ECSQARU
2005
Springer
16 years 6 days ago
Default Clustering from Sparse Data Sets
Categorization with a very high missing data rate is seldom studied, especially from a non-probabilistic point of view. This paper proposes a new algorithm called default clusterin...
Julien Velcin, Jean-Gabriel Ganascia
IDEAL
2004
Springer
16 years 1 days ago
The Application of K-Medoids and PAM to the Clustering of Rules
Abstract. Earlier research has resulted in the production of an ‘allrules’ algorithm for data-mining that produces all conjunctive rules of above given confidence and coverage...
Alan P. Reynolds, Graeme Richards, Victor J. Raywa...
FOCS
2000
IEEE
15 years 11 months ago
Clustering Data Streams
The data stream model has recently attracted attention for its applicability to numerous types of data, including telephone records, web documents and clickstreams. For analysis o...
Sudipto Guha, Nina Mishra, Rajeev Motwani, Liadan ...
ICML
1997
IEEE
15 years 10 months ago
Efficient Feature Selection in Conceptual Clustering
Feature selection has proven to be a valuable technique in supervised learning for improving predictive accuracy while reducing the number of attributes considered in a task. We i...
Mark Devaney, Ashwin Ram
SIGGRAPH
1995
ACM
15 years 10 months ago
Stochastic screening dithering with adaptive clustering
We developa clustereddithering methodthatusesstochasticscreening and is able to perform an adaptive variation of the cluster size. This makes it possible to achieve optimal rendit...
Luiz Velho, Jonas Gomes