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...

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Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence. - 1979. - 33(2011), 6 vom: 15. Juni, Seite 1217-33
1. Verfasser:	Cheng, Qiang (VerfasserIn)
Weitere Verfasser:	Zhou, Hongbo, Cheng, Jie
Format:	Online-Aufsatz
Sprache:	English
Veröffentlicht:	2011
Zugriff auf das übergeordnete Werk:	IEEE transactions on pattern analysis and machine intelligence
Schlagworte:	Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.