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Averaged boosting: A noise-robust ensemble method
- Averaged boosting: A noise-robust ensemble method
- Kim Y.
- Ewha Authors
- Issue Date
- Journal Title
- Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
- Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) vol. 2637, pp. 388 - 393
- Document Type
- Conference Paper
- A new noise robust ensemble method called "Averaged Boosting (A-Boosting)" is proposed. Using the hypothetical ensemble algorithm in Hilbert space, we explain that A-Boosting can be understood as a method of constructing a sequence of hypotheses and coefficients such that the average of the product of the base hypotheses and coefficients converges to the desirable function. Empirical studies showed that A-Boosting outperforms Bagging for low noise cases and is more robust than AdaBoost to label noise.
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- 자연과학대학 > 통계학전공 > Journal papers
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