Title :
Exploring constructive algorithms with stopping criteria to produce accurate and diverse individual neural networks in an ensemble
Author :
Islam, Md Monirul ; Shahjahan, Md ; Murase, K.
Author_Institution :
Dept. of Human & Artificial Intelligence Syst., Fukui Univ., Japan
Abstract :
Explores the use of constructive algorithms with stopping criteria to design accurate and diverse individual neural networks (NNs) in an ensemble. Based on constructive algorithms and stopping criteria, a constructive neural network ensemble (CNNE) method to design accurate and diverse individual NNs in an ensemble is proposed. The CNNE is applied to three benchmarked problems in NNs. They are cancer, diabetes and heart disease problems. The experimental results demonstrate the effectiveness of CNNE
Keywords :
cancer; learning (artificial intelligence); neural nets; patient diagnosis; cancer; constructive algorithms; constructive neural network ensemble method; diabetes; ensemble; generalization ability; heart disease; individual neural networks; stopping criteria; Algorithm design and analysis; Artificial intelligence; Artificial neural networks; Cancer; Cardiac disease; Design methodology; Diabetes; Humans; Neural networks; Training data;
Conference_Titel :
Systems, Man, and Cybernetics, 2001 IEEE International Conference on
Conference_Location :
Tucson, AZ
Print_ISBN :
0-7803-7087-2
DOI :
10.1109/ICSMC.2001.973500
