On Weak Base Hypotheses and Their Implications for Boosting Regression and Classification
When studying the training error and the prediction error for boosting, it is often assumed that the hypotheses returned by the base learner are weakly accurate, or are able to beat a random guesser by a certain amount of difference. It has been an open question how much this difference can be, whet...
| Veröffentlicht in: | The Annals of Statistics. - Institute of Mathematical Statistics. - 30(2002), 1, Seite 51-73 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2002
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| Zugriff auf das übergeordnete Werk: | The Annals of Statistics |
| Schlagworte: | Angular Span Boosting Classification Error Bounds Least Squares Regression Matching Pursuit Nearest Neighbor Rule Overfit Prediction Error Regularization mehr... |
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