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PRL
2006
77views more  PRL 2006»
15 years 3 months ago
Wavelet based approach to cluster analysis. Application on low dimensional data sets
In this paper, we present a wavelet based approach which tries to automatically find the number of clusters present in a data set, along with their position and statistical proper...
Xavier Otazu, Oriol Pujol
229
Voted
ADMI
2010
Springer
15 years 5 months ago
Clustering in a Multi-Agent Data Mining Environment
A Multi-Agent based approach to clustering using a generic Multi-Agent Data Mining (MADM) framework is described. The process use a collection of agents, running several different ...
Santhana Chaimontree, Katie Atkinson, Frans Coenen
126
Voted
ICML
2007
IEEE
16 years 4 months ago
Supervised clustering of streaming data for email batch detection
We address the problem of detecting batches of emails that have been created according to the same template. This problem is motivated by the desire to filter spam more effectivel...
Peter Haider, Ulf Brefeld, Tobias Scheffer
125
Voted
COCOON
2005
Springer
15 years 9 months ago
Algorithmic and Complexity Issues of Three Clustering Methods in Microarray Data Analysis
The complexity, approximation and algorithmic issues of several clustering problems are studied. These non-traditional clustering problems arise from recent studies in microarray ...
Jinsong Tan, Kok Seng Chua, Louxin Zhang
159
Voted
SDM
2009
SIAM
220views Data Mining» more  SDM 2009»
16 years 29 days ago
Bayesian Cluster Ensembles.
Cluster ensembles provide a framework for combining multiple base clusterings of a dataset to generate a stable and robust consensus clustering. There are important variants of th...
Hongjun Wang, Hanhuai Shan, Arindam Banerjee