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» Anytime Algorithm for Feature Selection
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ICML
2004
IEEE
16 years 2 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
CVPR
2008
IEEE
16 years 3 months ago
Integrated feature selection and higher-order spatial feature extraction for object categorization
In computer vision, the bag-of-visual words image representation has been shown to yield good results. Recent work has shown that modeling the spatial relationship between visual ...
David Liu, Gang Hua, Paul A. Viola, Tsuhan Chen
CIKM
2010
Springer
14 years 11 months ago
Regularization and feature selection for networked features
In the standard formalization of supervised learning problems, a datum is represented as a vector of features without prior knowledge about relationships among features. However, ...
Hongliang Fei, Brian Quanz, Jun Huan
AI
2004
Springer
15 years 1 months ago
A selective sampling approach to active feature selection
Feature selection, as a preprocessing step to machine learning, has been very effective in reducing dimensionality, removing irrelevant data, increasing learning accuracy, and imp...
Huan Liu, Hiroshi Motoda, Lei Yu
AMET
1998
Springer
15 years 6 months ago
Bid Evaluation and Selection in the MAGNET Automated Contracting System
We present an approach to the bid-evaluation problem in a system for multi-agent contract negotiation, called MAGNET. The MAGNET market infrastructure provides support for a variet...
Erik S. Steinmetz, John Collins, Scott Jamison, Ra...