An improved AdaBoost algorithm based on adaptive weight adjusting

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

Volumn 4632 LNAI, Issue , 2007, Pages 625-632

  Cheng, Lili ^a   Zhang, Jianpei ^a   Yang, Jing ^a   Ma, Jun ^a  

^a HARBIN ENGINEERING UNIVERSITY   (China)

Author keywords

Dynamic combination technology; Full information behavior correlation; Multiple classifiers combination

Indexed keywords

COMPUTATIONAL METHODS; COMPUTER SIMULATION; ITERATIVE METHODS; LEARNING ALGORITHMS; ADAPTIVE BOOSTING;

DYNAMIC COMBINATION TECHNOLOGY; FULL INFORMATION BEHAVIOR CORRELATION; MULTIPLE CLASSIFIERS COMBINATION; ADABOOST ALGORITHM; CLASSIFICATION PERFORMANCE; DYNAMIC COMBINATION; ENSEMBLE CLASSIFICATION; ENSEMBLE LEARNING ALGORITHM; FULL INFORMATIONS; SIMULATED EXPERIMENTS;

ADA (PROGRAMMING LANGUAGE); CLASSIFICATION (OF INFORMATION);

EID: 38049067229     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-73871-8_60     Document Type: Conference Paper

References (9)

1. Lu, X., Wang, Y., Jain, A.K: Combining Classifiers for Face Recognition. In: IEEE International Conference on Multimedia &Expo. pp. 13-16 (2003)
2. Dietrich, C., Schwenker, F., Palm, G.: Classification of time series utilizing temporal and decision fusion. In: Proceedings of Multiple Classifier Systems (MCS), pp. 378-387. Cambridge University Press, Cambridge (2001)
3. Xu, L., Krzyzak, A., Suen, C Y.: Method for Combing Multiple Classifiers and Their Applications to Handwriting Recognition. IEEE Transactions on Systems, Man, and Cybernetics 22, 418-435 (1992)
4. Freund, Y., Schapire, R.E.: Yoav Freund and Robert E Schapire: A decision-theoretic generalization of on-line learning to boosting. Journal of Computer and System Science 55, 119-139 (1997)
5. Freund, Y., Schapire, R.E.: Experiments with a new boosting algorithm. In: Machine Learning: Proceedings of the Thirteenth International Conference, pp. 148-156 (1996)
6. Puuronen, S., Terziyan, V., Tsymbal, A.: A dynamic integration algorithm for an ensemble of classifiers. In: Raś, Z.W., Skowron, A. (eds.) ISMIS 1999. LNCS, vol. 1609, Springer, Heidelberg (1999)
7. Tang, C.-S., Jin, Y.-H.: A Multiple Classifiers Integration Based on Adaptive Weight Adjusting and it's Application on text Classification. Computer Science 20, 82-84 (2003)
8. Tang, C.-S., Jin, Y.-H.: A Multiple Classifiers Integration Based on Full Information Matrix. Journal of Software 14, 1103-1109 (2003)
9. Jing, X., Ynag, J.: Combining Classifiers Based on Analysis of Correlation and Effective Supplement. Acta Automatica Sinica 26, 741-747 (2000)