Balancing between bagging and bumping

Advances in Neural Information Processing Systems

Volumn , Issue , 1997, Pages 466-472

  Heskes, Tom ^a  

^a RADBOUD UNIVERSITY NIJMEGEN   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

GENERALIZATION ERROR; GENERALIZATION PERFORMANCE; INDIVIDUAL NETWORK; QUADRATIC PROGRAMMING PROBLEMS; REAL-WORLD PROBLEM; REGRESSION PROBLEM; SALES FIGURE; WEIGHTING FACTORS;

STATISTICAL METHODS;

EID: 84898990528     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (9)

1. L. Breiman. Bagging predictors. Machine Learning, 24:123-140, 1996.
2. B. Efron and R. Tibshirani. An Introduction to the Bootstrap. Chapman & Hall, London,1993.
3. L. Hansen and P. Salomon. Neural network ensembles. IEEE Transactions on Pattern Analysis and Machine Intelligence, 12:993-1001, 1990.
4. T. Heskes. Practical confidence and prediction intervals. These proceedings, 1997.
5. R. Jacobs. Methods for combining experts probability assessments. Neural Computation, 7:867-888, 1995.
6. A. Krogh and J. Vedelsby. Neural network ensembles, cross validation, and active learning. In G. Tesauro, D. Touretzky, and T. Leen, editors, Advances in Neural Information Processing Systems 7, pages 231-238, Cambridge, 1995. MIT Press.
7. P. Sollich and A. Krogh. Learning with ensembles: How over-fitting can be useful. In D. Touretzky, M. Mozer, and M. Hasselmo, editors, Advances in Neural Information Processing Systems 8, pages 190-196, San Mateo, 1996. Morgan Kaufmann.
8. R. Tibshirani and K. Knight. Model search and inference by bootstrap "bumping". Technical report, University of Toronto, 1995.
9. D. Wolpert and W. Macready. Combining stacking with bagging to improve a learning algorithm. Technical report, Santa Fe Institute, Santa Fe, 1996.