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SGAI
2009
Springer

Remainder Subset Awareness for Feature Subset Selection

14 years 3 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 family of algorithms known as plus-l-minusr and its immediate derivatives (like forward selection) are very popular and often the only viable alternative when used in wrapper mode. In consequence, it is of the greatest importance to take the most of every evaluation of the inducer, which is normally the more costly part. In this paper, a technique is proposed that takes into account the inducer evaluation both in the current subset and in the remainder subset (its complementary set) and is applicable to any sequential subset selection algorithm at a reasonable overhead in cost. Its feasibility is demonstrated on a series of benchmark data sets.
Gabriel Prat-Masramon, Lluís A. Belanche Mu
Added 27 Jul 2010
Updated 27 Jul 2010
Type Conference
Year 2009
Where SGAI
Authors Gabriel Prat-Masramon, Lluís A. Belanche Muñoz
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