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» Study on Feature Selection Algorithm in Topic Tracking
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PR
2008
151views more  PR 2008»
14 years 9 months ago
Constraint Score: A new filter method for feature selection with pairwise constraints
Feature selection is an important preprocessing step in mining high-dimensional data. Generally, supervised feature selection methods with supervision information are superior to ...
Daoqiang Zhang, Songcan Chen, Zhi-Hua Zhou
89
Voted
ICML
2004
IEEE
15 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
PAMI
2007
156views more  PAMI 2007»
14 years 9 months ago
Selection and Fusion of Color Models for Image Feature Detection
—The choice of a color model is of great importance for many computer vision algorithms (e.g., feature detection, object recognition, and tracking) as the chosen color model indu...
Harro M. G. Stokman, Theo Gevers
82
Voted
ECCV
2002
Springer
15 years 11 months ago
Fusion of Multiple Tracking Algorithms for Robust People Tracking
This paper shows how the output of a number of detection and tracking algorithms can be fused to achieve robust tracking of people in an indoor environment. The new tracking system...
Nils T. Siebel, Stephen J. Maybank
AI
2004
Springer
14 years 9 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