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ICPR
2004
IEEE
14 years 8 months ago
Large Scale Feature Selection Using Modified Random Mutation Hill Climbing
Feature selection is a critical component of many pattern recognition applications. There are two distinct mechanisms for feature selection, namely the wrapper method and the filt...
Anil K. Jain, Michael E. Farmer, Shweta Bapna
AI
2009
Springer
14 years 2 months ago
An Iterative Hybrid Filter-Wrapper Approach to Feature Selection for Document Clustering
The manipulation of large-scale document data sets often involves the processing of a wealth of features that correspond with the available terms in the document space. The employm...
Mohammad-Amin Jashki, Majid Makki, Ebrahim Bagheri...
KDD
1995
ACM
133views Data Mining» more  KDD 1995»
13 years 11 months ago
Feature Subset Selection Using the Wrapper Method: Overfitting and Dynamic Search Space Topology
In the wrapperapproachto feature subset selection, a searchfor an optimalset of features is madeusingthe induction algorithm as a black box. Theestimated future performanceof the ...
Ron Kohavi, Dan Sommerfield
SGAI
2004
Springer
14 years 26 days ago
Overfitting in Wrapper-Based Feature Subset Selection: The Harder You Try the Worse it Gets
In Wrapper based feature selection, the more states that are visited during the search phase of the algorithm the greater the likelihood of finding a feature subset that has a high...
John Loughrey, Padraig Cunningham
TNN
2008
133views more  TNN 2008»
13 years 7 months ago
A General Wrapper Approach to Selection of Class-Dependent Features
In this paper, we argue that for a C-class classification problem, C 2-class classifiers, each of which discriminating one class from the other classes and having a characteristic ...
Lipo Wang, Nina Zhou, Feng Chu