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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 7 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 1 months 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