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CVPR
2005
IEEE
16 years 8 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
JSS
2008
94views more  JSS 2008»
15 years 6 months ago
Examining the significance of high-level programming features in source code author classification
The use of Source Code Author Profiles (SCAP) represents a new, highly accurate approach to source code authorship identification that is, unlike previous methods, language indepe...
Georgia Frantzeskou, Stephen G. MacDonell, Efstath...
TKDE
2008
111views more  TKDE 2008»
15 years 6 months ago
Text Clustering with Feature Selection by Using Statistical Data
Abstract-- Feature selection is an important method for improving the efficiency and accuracy of text categorization algorithms by removing redundant and irrelevant terms from the ...
Yanjun Li, Congnan Luo, Soon M. Chung
SIGIR
2009
ACM
16 years 19 days ago
The impact of crawl policy on web search effectiveness
Crawl selection policy has a direct influence on Web search effectiveness, because a useful page that is not selected for crawling will also be absent from search results. Yet th...
Dennis Fetterly, Nick Craswell, Vishwa Vinay
DAGSTUHL
2009
15 years 7 months ago
Advances in Feature Selection with Mutual Information
The selection of features that are relevant for a prediction or classification problem is an important problem in many domains involving high-dimensional data. Selecting features h...
Michel Verleysen, Fabrice Rossi, Damien Fran&ccedi...