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ICML
2004
IEEE
14 years 10 months ago
Text categorization with many redundant features: using aggressive feature selection to make SVMs competitive with C4.5
Text categorization algorithms usually represent documents as bags of words and consequently have to deal with huge numbers of features. Most previous studies found that the major...
Evgeniy Gabrilovich, Shaul Markovitch
INFOCOM
2008
IEEE
14 years 4 months ago
Characterizing and Modelling Clustering Features in AS-Level Internet Topology
The AS-level Internet topology has shown significant clustering features. In this paper, we propose a new set of clustering metrics and conduct extensive measurement on the AS-le...
Yan Li, Jun-Hong Cui, Dario Maggiorini, Michalis F...
PKDD
2009
Springer
152views Data Mining» more  PKDD 2009»
14 years 4 months ago
Feature Selection for Value Function Approximation Using Bayesian Model Selection
Abstract. Feature selection in reinforcement learning (RL), i.e. choosing basis functions such that useful approximations of the unkown value function can be obtained, is one of th...
Tobias Jung, Peter Stone
CRV
2005
IEEE
201views Robotics» more  CRV 2005»
14 years 3 months ago
Minimum Bayes Error Features for Visual Recognition by Sequential Feature Selection and Extraction
The extraction of optimal features, in a classification sense, is still quite challenging in the context of large-scale classification problems (such as visual recognition), inv...
Gustavo Carneiro, Nuno Vasconcelos
TREC
2004
13 years 11 months ago
Feature Generation, Feature Selection, Classifiers, and Conceptual Drift for Biomedical Document Triage
We approached the problem of classifying papers for the TREC 2004 Genomics Track triage task as a four step process: feature generation, feature selection, classifier training, an...
Aaron M. Cohen, Ravi Teja Bhupatiraju, William R. ...