DocumentCode
342607
Title
A genetic constructive induction model
Author
Kuscu, Ibrahim
Author_Institution
Sch. of Cognitive & Comput. Sci., Sussex Univ., Brighton, UK
Volume
1
fYear
1999
fDate
1999
Abstract
A hybrid model which uses genetic programming as part of a constructive induction system for supervised learning tasks is presented. The results of the experiments suggest that the model is an effective tool for increasing the generalisation performance of backpropagation in solving parity problems. The model also offers a potentially strong approach to solve problems of data mining
Keywords
backpropagation; data mining; generalisation (artificial intelligence); genetic algorithms; backpropagation; data mining; generalisation performance; genetic constructive induction model; genetic programming; hybrid model; parity problems; supervised learning tasks; Backpropagation algorithms; Data mining; Decision trees; Feedforward neural networks; Feeds; Genetic programming; Learning systems; Neural networks; Supervised learning; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 1999. CEC 99. Proceedings of the 1999 Congress on
Conference_Location
Washington, DC
Print_ISBN
0-7803-5536-9
Type
conf
DOI
10.1109/CEC.1999.781928
Filename
781928
Link To Document