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ICML
2000
IEEE
15 years 10 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
86
Voted
IJBRA
2007
97views more  IJBRA 2007»
14 years 9 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
15 years 10 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
15 years 2 months 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»
14 years 9 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