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Frénay et al., 2014 - Google Patents

Estimating mutual information for feature selection in the presence of label noise

Frénay et al., 2014

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Document ID
6734715295594740113
Author
Frénay B
Doquire G
Verleysen M
Publication year
Publication venue
Computational Statistics & Data Analysis

External Links

Snippet

A way to achieve feature selection for classification problems polluted by label noise is proposed. The performances of traditional feature selection algorithms often decrease sharply when some samples are wrongly labelled. A method based on a probabilistic label …
Continue reading at perso.uclouvain.be (PDF) (other versions)

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    • G06K9/6228—Selecting the most significant subset of features
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