Title :
Incremental neural learning using AdaBoost
Author :
Murphey, Yi L. ; Chen, Zhihang ; Feldkamp, Lee
Author_Institution :
Dept. of Electr. & Comput. Eng., Michigan Univ., Dearborn, MI, USA
fDate :
6/24/1905 12:00:00 AM
Abstract :
An incremental learning system updates its hypotheses as new instances arrive without reexamining old instances. This paper describes our research in incremental neural learning. We developed an incremental neural learning (INL) framework that allows a neural network system to incrementally learn new knowledge from only new data without forgetting the existing knowledge. We have applied the INL to a vehicle fault diagnostics problem and our experiments showed very positive results
Keywords :
Ada; learning (artificial intelligence); neural nets; AdaBoost; INL framework; incremental learning; incremental neural learning; neural network system; vehicle fault diagnostics problem; Backpropagation; Decision trees; Knowledge management; Learning systems; Machine learning; Manufacturing industries; Manufacturing processes; Neural networks; Real time systems; Vehicles;
Conference_Titel :
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7278-6
DOI :
10.1109/IJCNN.2002.1007501
