An ensemble technique for stable learners with performance bounds

Proceedings of the National Conference on Artificial Intelligence

Volumn , Issue , 2004, Pages 330-335

  Davidson, Ian ^a  

^a State University of New York   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DECISION TREES; ENSEMBLE TECHNIQUES; OPTIMAL BAYES CLASSIFIER (OBC); POSTERIOR DENSITY FUNCTIONS;

ALGORITHMS; CHEBYSHEV APPROXIMATION; COMPUTER SCIENCE; DATA ACQUISITION; ERROR ANALYSIS; PROBABILITY DISTRIBUTIONS;

LEARNING SYSTEMS;

EID: 9444278378     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (10)

1. Brieman, L., Bagging Predictors, Machine Learning 1996.
2. Breiman, L., Arcing classifiers. Ann. Statistics,26(3), 1998.
3. Clarke B. and Barron A. Entropy, risk and the Bayesian central limit theorem. manuscript.
4. Domingos, P., Bayesian Averaging of Classifiers and the Overfilling Problem. ICML, 2000.
5. Duda R., Hart P., & Stork D., Pattern Classification. Wiley, 2001.
6. Efron, B. 1979. Bootstrap methods. Annals Statistics 7:1-26.
7. Krogh A. and Vedelsby J., Neural network ensembles, cross validation and active learning. NIPS 1995.
8. Melville, P. and Mooney, R. Constructing Diverse Classifier Ensembles Using Artificial Training Examples, IJCAI 2003.
9. Mitchell, T. (1997), Machine Learning, McGraw Hill.
10. Schapire R.E. The strength of weak learnability. Machine Learning, 5(2):197-227, 1990.