Regularizing AdaBoost

Advances in Neural Information Processing Systems

Volumn , Issue , 1999, Pages 564-570

  Rätsch, Gunnar ^a   Onoda, Takashi ^a,b   Müller, Klaus R ^a  

^a FRAUNHOFER FIRST   (Germany)

^b CENTRAL RESEARCH INSTITUTE OF ELECTRIC POWER INDUSTRY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS;

BOOSTING METHOD; CLASSIFICATION MARGINS; LOW NOISE; NOISY DATA; OVERFITTING; SLACK VARIABLES; SOFT MARGINS;

ADAPTIVE BOOSTING;

EID: 0001102148     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (14)

1. C. M. Bishop. Neural Networks for Pattern Recognition. Clarendon, 1995.
2. L. Breiman. Bagging predictors. Machine Learning, 26(2):123-140, 1996.
3. L. Breiman. Arcing classifiers. Tech. Rep. 460, Berkeley Stat. Dept., 1997.
4. L. Breiman. Prediction games and arcing algorithms. Tech. Rep. 504, Berkeley Stat. Dept., 1997.
5. C. Cortes, V. Vapnik. Support vector network. Mach. Learn., 20:273-297, 1995.
6. R. Schapire, Y. Singer. Improved Boosting Algorithms Using Confidence-rated Predictions. In Proc. of COLT'98.
7. A.J. Grove, D. Schuurmans. Boosting in the limit: Maximizing the margin of learned ensembles. In Proc. 15th Nat. Conf. on AI, 1998. To appear.
8. Y. LeCun et al. Learning algorithms for classification: A comparism on handwritten digit recognistion. Neural Networks, pages 261-276, 1995.
9. T. Onoda, G. Ratsch, and K.-R. Müller. An asymptotic analysis of adaboost in the binary classification case. In Proc. of ICANN'98, April 1998.
10. J. Quinlan. Boosting first-order learning. In Proc. of the 7th Internat. Workshop on Algorithmic Learning Theory, LNAI, 1160, 143-155. Springer.
11. G. Ratsch. Soft Margins for AdaBoost. August 1998. Royal Holloway College, Technical Report NC-TR-1998-021. Submitted to Machine Learning.
12. R. Schapire, Y. Freund, P. Bartlett, W. Lee. Boosting the margin: A new explanation for the effectiveness of voting methods. Mach. Learn., 148-156, 1998.
13. H. Schwenk and Y. Bengio. "Adaboosting neural networks: Application to online character recognition. In ICANN'97, LNCS, 1327, 967-972, 1997. Springer.
14. V. Vapnik. The Nature of Statistical Learning Theory. Springer, 1995.