Performance degradation in boosting

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2096, Issue , 2001, Pages 11-21

  Wickramaratna, Jeevani ^a   Holden, Sean ^a   Buxton, Bernard ^a  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

PRODUCTIVITY;

HIGH PRODUCTIVITY; INDIVIDUAL CLASSIFIERS; MODEL SELECTION; PERFORMANCE DEGRADATION; PERFORMANCE LEVEL; PRODUCTIVITY INCREASE; TRAINING SAMPLE; WEAK LEARNER;

ADAPTIVE BOOSTING;

EID: 84956981949     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-48219-9_2     Document Type: Conference Paper

References (6)

1. Freund, Yoav & Schapire, Robert E.: A Brief Introduction to Boosting. Proceedings of the Sixteenth International Joint Conference on Artificial intelligence.
2. Freund, Yoav & Schapire, Robert E.: Discussions of the paper’’Arching Classifiers” by Leo Brieman. The Annals of Statistics, 26(3):824-832.
3. Wickramaratna, Holden & Deepa Buxton: Efects of the Strength of the Weak Learner in Boosting Kernel Machines. Submitted to the Journal of Machine Learning Research.
4. Onoda, T., Ratsch, G. & Muller, K.: An Asymptotic Analysis of AdaBoost in the Binary Classification Case. GMD FIRSTs Rudower Chaussee, Germany.
5. Quinlan, J.: Bagging, Boosting and C4.5. National Conference on Artificial Intelligence.
6. Schapire, Robert E.: Theoretical Views of Boosting and Applications. Proceedings of Algorithmic Learning Theory.