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ICPR
2008
IEEE
14 years 3 months ago
Semi-supervised feature selection under logistic I-RELIEF framework
We consider feature selection in the semi-supervised learning setting. This problem is rarely addressed in the literature. We propose a new algorithm as a natural extension of the...
Yubo Cheng, Yunpeng Cai, Yijun Sun, Jian Li
ADMA
2006
Springer
139views Data Mining» more  ADMA 2006»
14 years 3 months ago
Semantic Scoring Based on Small-World Phenomenon for Feature Selection in Text Mining
This paper proposes an effective scoring scheme for feature selection in Text Mining, using characteristics of Small-World Phenomenon on the semantic networks of documents. Our foc...
Chong Huang, YongHong Tian, Tiejun Huang, Wen Gao
RSFDGRC
2005
Springer
111views Data Mining» more  RSFDGRC 2005»
14 years 2 months ago
Feature Selection with Adjustable Criteria
Abstract. We present a study on a rough set based approach for feature selection. Instead of using significance or support, Parameterized Average Support Heuristic (PASH) consider...
Jingtao Yao, Ming Zhang
ICDM
2002
IEEE
448views Data Mining» more  ICDM 2002»
14 years 2 months ago
Feature Selection Algorithms: A Survey and Experimental Evaluation
In view of the substantial number of existing feature selection algorithms, the need arises to count on criteria that enables to adequately decide which algorithm to use in certai...
Luis Carlos Molina, Lluís Belanche, À...
ICTAI
1992
IEEE
14 years 1 months ago
Genetic Algorithms as a Tool for Feature Selection in Machine Learning
This paper describes an approach being explored to improve the usefulness of machine learning techniques for generating classification rules for complex, real world data. The appr...
Haleh Vafaie, Kenneth A. De Jong