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» Wrapper for Ranking Feature Selection
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ICML
2000
IEEE
14 years 8 months ago
Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning
Algorithms for feature selection fall into two broad categories: wrappers that use the learning algorithm itself to evaluate the usefulness of features and filters that evaluate f...
Mark A. Hall
IJBRA
2007
97views more  IJBRA 2007»
13 years 7 months ago
Structural Risk Minimisation based gene expression profiling analysis
: For microarray based cancer classification, feature selection is a common method for improving classifier generalisation. Most wrapper methods use cross validation methods to eva...
Xue-wen Chen, Byron Gerlach, Dechang Chen, ZhenQiu...
ICML
2001
IEEE
14 years 8 months ago
Feature selection for high-dimensional genomic microarray data
We report on the successful application of feature selection methods to a classification problem in molecular biology involving only 72 data points in a 7130 dimensional space. Ou...
Eric P. Xing, Michael I. Jordan, Richard M. Karp
SGAI
2009
Springer
14 years 2 days ago
Remainder Subset Awareness for Feature Subset Selection
Feature subset selection has become more and more a common topic of research. This popularity is partly due to the growth in the number of features and application domains. The fa...
Gabriel Prat-Masramon, Lluís A. Belanche Mu...
PR
2006
111views more  PR 2006»
13 years 7 months ago
The Bhattacharyya space for feature selection and its application to texture segmentation
A feature selection methodology based on a novel Bhattacharyya space is presented and illustrated with a texture segmentation problem. The Bhattacharyya space is constructed from ...
Constantino Carlos Reyes-Aldasoro, Abhir Bhalerao