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SYNASC
2005
IEEE
170views Algorithms» more  SYNASC 2005»
15 years 7 months ago
Density Based Clustering with Crowding Differential Evolution
The aim of this work is to analyze the applicability of crowding differential evolution to unsupervised clustering. The basic idea of this approach, interpreting the clustering pr...
Daniela Zaharie
ICPR
2008
IEEE
15 years 7 months ago
Multi-stage branch-and-bound for maximum variance disparity clustering
A split-and-merge framework based on a maximum variance criterion is proposed for disparity clustering. The proposed algorithm transforms low-level stereo disparity information to...
Ninad Thakoor, Venkat Devarajan, Jean Gao
ICASSP
2008
IEEE
15 years 7 months ago
Unsupervised validity measures for vocalization clustering
This paper describes unsupervised speech/speaker cluster validity measures based on a dissimilarity metric, for the purpose of estimating the number of clusters in a speech data s...
Kuntoro Adi, Kristine E. Sonstrom, Peter M. Scheif...
KDD
2003
ACM
191views Data Mining» more  KDD 2003»
16 years 1 months ago
Assessment and pruning of hierarchical model based clustering
The goal of clustering is to identify distinct groups in a dataset. The basic idea of model-based clustering is to approximate the data density by a mixture model, typically a mix...
Jeremy Tantrum, Alejandro Murua, Werner Stuetzle
SMC
2007
IEEE
110views Control Systems» more  SMC 2007»
15 years 7 months ago
A validity index based on cluster symmetry
— An important consideration in clustering is the determination of the correct number of clusters and the appropriate partitioning of a given data set. In this paper, a newly dev...
Sriparna Saha, Sanghamitra Bandyopadhyay