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A comparative evaluation of sequential feature selection algorithms

by: David W Aha, Richard L Bankert

edited by: Douglas H Fisher, Hans-Joachim Lenz

(1996), pp. 199-206.


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Several recent machine learning publications demonstrate the utility of using feature selection algorithms in supervised learning tasks. Among these, sequential feature selection algorithms are receiving attention. The most frequently studied variants of these algorithms are forward and backward sequential selection. Many studies on supervised learning with sequential feature selection report applications of these algorithms, but do not consider variants of them that might be more appropriate...


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