An Introduction to Variable and Feature Selection
Isabelle Guyon, André Elisseeff;
3(Mar):1157-1182, 2003.
Abstract
Variable and feature selection have become the focus of much
research in areas of application for which datasets with tens or
hundreds of thousands of variables are available. These areas
include text processing of internet documents, gene expression
array analysis, and combinatorial chemistry. The objective of
variable selection is three-fold: improving the prediction
performance of the predictors, providing faster and more
cost-effective predictors, and providing a better understanding of
the underlying process that generated the data. The contributions
of this special issue cover a wide range of aspects of such
problems: providing a better definition of the objective function,
feature construction, feature ranking, multivariate feature
selection, efficient search methods, and feature validity
assessment methods.
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