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» Memetic Algorithms for Feature Selection on Microarray Data
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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
ICML
2009
IEEE
14 years 8 months ago
Regularization and feature selection in least-squares temporal difference learning
We consider the task of reinforcement learning with linear value function approximation. Temporal difference algorithms, and in particular the Least-Squares Temporal Difference (L...
J. Zico Kolter, Andrew Y. Ng
CIDM
2007
IEEE
14 years 1 months ago
Mining Subspace Correlations
— In recent applications of clustering such as gene expression microarray analysis, collaborative filtering, and web mining, object similarity is no longer measured by physical ...
Rave Harpaz, Robert M. Haralick
DMIN
2007
203views Data Mining» more  DMIN 2007»
13 years 9 months ago
Evaluation of Feature Selection Techniques for Analysis of Functional MRI and EEG
— The application of feature selection techniques greatly reduces the computational cost of classifying highdimensional data. Feature selection algorithms of varying performance ...
Lauren Burrell, Otis Smart, George J. Georgoulas, ...
SLSFS
2005
Springer
14 years 1 months ago
Random Projection, Margins, Kernels, and Feature-Selection
Random projection is a simple technique that has had a number of applications in algorithm design. In the context of machine learning, it can provide insight into questions such as...
Avrim Blum