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» An objective evaluation criterion for clustering
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KDD
2004
ACM
103views Data Mining» more  KDD 2004»
14 years 5 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
CIKM
1999
Springer
13 years 9 months ago
Clustering Transactions Using Large Items
In traditional data clustering, similarity of a cluster of objects is measured by pairwise similarity of objects in that cluster. We argue that such measures are not appropriate f...
Ke Wang, Chu Xu, Bing Liu
CIKM
2004
Springer
13 years 10 months ago
Soft clustering criterion functions for partitional document clustering: a summary of results
Recently published studies have shown that partitional clustering algorithms that optimize certain criterion functions, which measure key aspects of inter- and intra-cluster simil...
Ying Zhao, George Karypis
CIT
2007
Springer
13 years 11 months ago
Performance Assessment of Some Clustering Algorithms Based on a Fuzzy Granulation-Degranulation Criterion
In this paper a fuzzy quantization dequantization criterion is used to propose an evaluation technique to determine the appropriate clustering algorithm suitable for a particular ...
Sriparna Saha, Sanghamitra Bandyopadhyay
PRL
1998
142views more  PRL 1998»
13 years 4 months ago
A monothetic clustering method
: The proposed divisive clustering method performs simultaneously a hierarchy of a set of objects and a monothetic characterization of each cluster of the hierarchy. A division is ...
Marie Chavent