AutoEval : Are Labels Always Necessary for Classifier Accuracy Evaluation?
Understanding model decision under novel test scenarios is central to the community. A common practice is evaluating models on labeled test sets. However, many real-world scenarios see unlabeled test data, rendering the common supervised evaluation protocols infeasible. In this paper, we investigate...
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 46(2024), 3 vom: 15. Feb., Seite 1868-1880 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
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2024
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence |
| Schlagworte: | Journal Article |
| Online verfügbar |
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