Incremental neural learning using AdaBoost

Proceedings of the International Joint Conference on Neural Networks

Volumn 3, Issue , 2002, Pages 2304-2309

  Murphey, Yi Lu ^a   Chen, ZhiHang ^a   Feldkamp, Lee ^a  

^a UNIVERSITY OF MICHIGAN DEARBORN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BACKPROPAGATION; FAULT TOLERANT COMPUTER SYSTEMS; LEARNING ALGORITHMS; LEARNING SYSTEMS; PATTERN RECOGNITION; TREES (MATHEMATICS);

ADABOOST; INCREMENTAL BACK PROPAGATION LEARNING NETWORKS; INCREMENTAL NEURAL LEARNING; VEHICLE FAULT DIAGNOSTIC PROBLEM;

NEURAL NETWORKS;

EID: 0036086762     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (12)

1. Incremental induction of decision trees
2. Incremental backpropagation learning networks
3. An incremental adaptive network for online supervised learning and probability estimation
4. A neural network architecture for incremental learning
5. An incremental unsupervised learning scheme for function approximation
6. A decision-theoretic generalization of online learning and an application to boosting
7. A brief introduction to boosting
8. Theoretical views of boosting and applications
9. IEEE Transaction on Vehicular
10. A fuzzy system for automotive fault diagnosis: - Fast rule generation and self-tuning
11. Neural learning from unbalanced data using noise modeling