Title :
Rule learning based on neural network ensemble
Author :
Jiang, Yuan ; Zhou, Zhi-Hua ; Chen, Zhao-Qian
Author_Institution :
Nat. Lab. for Novel Software Technol., Nanjing Univ., China
fDate :
6/24/1905 12:00:00 AM
Abstract :
A neural network ensemble can significantly improve the generalization ability of neural network-based systems. In this paper, a novel rule-learning algorithm is proposed where the neural network ensemble acts as a front-end processor that generates data for the learning of rules. Experimental results show that the proposed algorithm can generate rules with strong generalization ability
Keywords :
generalisation (artificial intelligence); learning (artificial intelligence); neural nets; data generation; front-end processor; generalization ability; neural network ensemble; rule learning algorithm; Character recognition; Decision trees; Face recognition; Laboratories; Learning systems; Logic programming; Machine learning; Machine learning algorithms; Matrix converters; Neural networks;
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.2002.1007724
