The Fisher-Markov selector : fast selecting maximally separable feature subset for multiclass classification with applications to high-dimensional data
Selecting features for multiclass classification is a critically important task for pattern recognition and machine learning applications. Especially challenging is selecting an optimal subset of features from high-dimensional data, which typically have many more variables than observations and cont...
| Publié dans: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 33(2011), 6 vom: 15. Juni, Seite 1217-33 |
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| Auteur principal: | |
| Autres auteurs: | , |
| Format: | Article en ligne |
| Langue: | English |
| Publié: |
2011
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| Accès à la collection: | IEEE transactions on pattern analysis and machine intelligence |
| Sujets: | Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S. |
| Accès en ligne |
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