Semi-Supervised Discriminative Classification Robust to Sample-Outliers and Feature-Noises
Discriminative methods commonly produce models with relatively good generalization abilities. However, this advantage is challenged in real-world applications (e.g., medical image analysis problems), in which there often exist outlier data points (sample-outliers) and noises in the predictor values...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 41(2019), 2 vom: 18. Feb., Seite 515-522
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| 1. Verfasser: |
Adeli, Ehsan
(VerfasserIn) |
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| Weitere Verfasser: |
Thung, Kim-Han,
An, Le,
Wu, Guorong,
Shi, Feng,
Wang, Tao,
Shen, Dinggang |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2019
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence
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| Schlagworte: | Journal Article
Research Support, N.I.H., Extramural |
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