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CSB
2005
IEEE
115views Bioinformatics» more  CSB 2005»
14 years 1 months ago
A New Clustering Strategy with Stochastic Merging and Removing Based on Kernel Functions
With hierarchical clustering methods, divisions or fusions, once made, are irrevocable. As a result, when two elements in a bottom-up algorithm are assigned to one cluster, they c...
Huimin Geng, Hesham H. Ali
PAMI
2002
106views more  PAMI 2002»
13 years 7 months ago
Performance Evaluation of Some Clustering Algorithms and Validity Indices
In this article, we evaluate the performance of three clustering algorithms, hard K-Means, single linkage, and a simulated annealing (SA) based technique, in conjunction with four ...
Ujjwal Maulik, Sanghamitra Bandyopadhyay
MICAI
2007
Springer
14 years 2 months ago
Fuzzifying Clustering Algorithms: The Case Study of MajorClust
Among various document clustering algorithms that have been proposed so far, the most useful are those that automatically reveal the number of clusters and assign each target docum...
Eugene Levner, David Pinto, Paolo Rosso, David Alc...
ICDM
2006
IEEE
86views Data Mining» more  ICDM 2006»
14 years 2 months ago
Turning Clusters into Patterns: Rectangle-Based Discriminative Data Description
The ultimate goal of data mining is to extract knowledge from massive data. Knowledge is ideally represented as human-comprehensible patterns from which end-users can gain intuiti...
Byron J. Gao, Martin Ester
CIARP
2008
Springer
13 years 10 months ago
Cluster Stability Assessment Based on Theoretic Information Measures
Abstract. Cluster validation to determine the right number of clusters is an important issue in clustering processes. In this work, a strategy to address the problem of cluster val...
Damaris Pascual, Filiberto Pla, José Salvad...