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» On the Performance of Ant-based Clustering
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KDD
2004
ACM
103views Data Mining» more  KDD 2004»
16 years 6 months ago
An objective evaluation criterion for clustering
We propose and test an objective criterion for evaluation of clustering performance: How well does a clustering algorithm run on unlabeled data aid a classification algorithm? The...
Arindam Banerjee, John Langford
GECCO
2006
Springer
144views Optimization» more  GECCO 2006»
15 years 10 months ago
On semi-supervised clustering via multiobjective optimization
Semi-supervised classification uses aspects of both unsupervised and supervised learning to improve upon the performance of traditional classification methods. Semi-supervised clu...
Julia Handl, Joshua D. Knowles
ICML
2006
IEEE
16 years 7 months ago
Discriminative cluster analysis
Clustering is one of the most widely used statistical tools for data analysis. Among all existing clustering techniques, k-means is a very popular method because of its ease of pr...
Fernando De la Torre, Takeo Kanade
WWW
2007
ACM
16 years 7 months ago
A clustering method for web data with multi-type interrelated components
Traditional clustering algorithms work on "flat" data, making the assumption that the data instances can only be represented by a set of homogeneous and uniform features...
Levent Bolelli, Seyda Ertekin, Ding Zhou, C. Lee G...
ICMCS
2007
IEEE
159views Multimedia» more  ICMCS 2007»
16 years 17 days ago
Boosting Face Retrieval by using Relevant Set Correlation Clustering
We present a method to improve the performance of face retrieval in news videos by using the relevant-set correlation (RSC) clustering model. In this method, faces of a person are...
Duy-Dinh Le, Shin'ichi Satoh, Michael E. Houle