Sciweavers

484 search results - page 22 / 97
» Measuring the Quality of Approximated Clusterings
Sort
View
CVPR
2005
IEEE
16 years 3 months ago
A Bayesian Approach to Unsupervised Feature Selection and Density Estimation Using Expectation Propagation
We propose an approximate Bayesian approach for unsupervised feature selection and density estimation, where the importance of the features for clustering is used as the measure f...
Shaorong Chang, Nilanjan Dasgupta, Lawrence Carin
138
Voted
IAT
2009
IEEE
15 years 8 months ago
Cluster-Swap: A Distributed K-median Algorithm for Sensor Networks
In building practical sensor networks, it is often beneficial to use only a subset of sensors to take measurements because of computational, communication, and power limitations....
Yoonheui Kim, Victor R. Lesser, Deepak Ganesan, Ra...
CIT
2007
Springer
15 years 8 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
128
Voted
FOCS
2000
IEEE
15 years 6 months ago
On Clusterings - Good, Bad and Spectral
We motivate and develop a natural bicriteria measure for assessing the quality of a clustering that avoids the drawbacks of existing measures. A simple recursive heuristic is shown...
Ravi Kannan, Santosh Vempala, Adrian Vetta
ESWS
2008
Springer
15 years 3 months ago
Conceptual Clustering and Its Application to Concept Drift and Novelty Detection
Abstract. The paper presents a clustering method which can be applied to populated ontologies for discovering interesting groupings of resources therein. The method exploits a simp...
Nicola Fanizzi, Claudia d'Amato, Floriana Esposito