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8

PPSN
2004
Springer

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135views Distributed And Parallel Com...» more PPSN 2004»

Ensemble Learning with Evolutionary Computation: Application to Feature Ranking

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Ensemble Learning with Evolutionary Computation: Application to Feature Ranking

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Abstract. Exploiting the diversity of hypotheses produced by evolutionary learning, a new ensemble approach for Feature Selection is presented, aggregating the feature rankings extracted from the hypotheses. A statistical model is devised to enable the direct evaluation of the approach; comparative experimental results show its good behavior on non-linear concepts when the features outnumber the examples.

Kees Jong, Elena Marchiori, Michèle Sebag

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Distributed And Parallel Computing | Feature Rankings | Feature Selection | Non-linear Concepts | PPSN 2004 |

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Added	02 Jul 2010
Updated	02 Jul 2010
Type	Conference
Year	2004
Where	PPSN
Authors	Kees Jong, Elena Marchiori, Michèle Sebag

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