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TKDE
2008
197views more  TKDE 2008»
14 years 10 months ago
Agglomerative Fuzzy K-Means Clustering Algorithm with Selection of Number of Clusters
In this paper, we present an agglomerative fuzzy K-Means clustering algorithm for numerical data, an extension to the standard fuzzy K-Means algorithm by introducing a penalty term...
Mark Junjie Li, Michael K. Ng, Yiu-ming Cheung, Jo...
94
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CSDA
2007
103views more  CSDA 2007»
14 years 10 months ago
Cluster-wise assessment of cluster stability
Stability in cluster analysis is strongly dependent on the data set, especially on how well separated and how homogeneous the clusters are. In the same clustering, some clusters m...
Christian Hennig
IJCNN
2006
IEEE
15 years 4 months ago
An Evaluation of Over-Fit Control Strategies for Multi-Objective Evolutionary Optimization
— The optimization of classification systems is often confronted by the solution over-fit problem. Solution over-fit occurs when the optimized classifier memorizes the traini...
Paulo Vinicius Wolski Radtke, Tony Wong, Robert Sa...
CODES
2004
IEEE
15 years 2 months ago
Multi-objective mapping for mesh-based NoC architectures
In this paper we present an approach to multi-objective exploration of the mapping space of a mesh-based network-on-chip architecture. Based on evolutionary computing techniques, ...
Giuseppe Ascia, Vincenzo Catania, Maurizio Palesi
94
Voted
ICDM
2006
IEEE
129views Data Mining» more  ICDM 2006»
15 years 4 months ago
Consensus Clustering for Detection of Overlapping Clusters in Microarray Data
Most clustering algorithms are partitional in nature, assigning each data point to exactly one cluster. However, several real world datasets have inherently overlapping clusters i...
Meghana Deodhar, Joydeep Ghosh