Title :
Experiments with the cascade-correlation algorithm
Author :
Yang, Jihoon ; Honavar, Vasant
Author_Institution :
Dept. of Comput. Sci., Iowa State Univ., Ames, IA, USA
Abstract :
A series of experiments with the cascade-correlation algorithm (CCA) and some of its variants on a number of real-world pattern classification tasks are described. Some of the experiments investigated the effect of different design parameters on the performance of the CCA. Parameter settings that consistently yield good performance on different data sets were identified. The performance of the CCA is compared with that of the backpropagation algorithm and the perceptron algorithm. Preliminary results obtained from some variants of CCA and some directions for future work with CCA-like neural network learning methods are discussed
Keywords :
correlation theory; learning systems; neural nets; pattern recognition; cascade-correlation algorithm; neural network learning methods; real-world pattern classification; Approximation algorithms; Ash; Backpropagation algorithms; Computer science; Function approximation; Learning systems; Machine learning; Neural networks; Pattern classification; Testing;
Conference_Titel :
Neural Networks, 1991. 1991 IEEE International Joint Conference on
Print_ISBN :
0-7803-0227-3
DOI :
10.1109/IJCNN.1991.170752
