Ranking a Random Feature for Variable and Feature Selection
Hervé Stoppiglia, Gérard Dreyfus, Rémi Dubois, Yacine Oussar;
3(Mar):1399-1414, 2003.
Abstract
We describe a feature selection method that can be applied directly to
models that are linear with respect to their parameters, and indirectly to
others. It is independent of the target machine. It is closely related to
classical statistical hypothesis tests, but it is more intuitive, hence more
suitable for use by engineers who are not statistics experts. Furthermore,
some assumptions of classical tests are relaxed. The method has been used
successfully in a number of applications that are briefly described.
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