Experiments with the cascade-correlation algorithm

Jihoon Yang, Vasant Honavar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

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.

Original languageEnglish (US)
Title of host publication91 IEEE Int Jt Conf Neural Networks IJCNN 91
PublisherPubl by IEEE
Pages2428-2433
Number of pages6
ISBN (Print)0780302273
StatePublished - Dec 1 1991
Event1991 IEEE International Joint Conference on Neural Networks - IJCNN '91 - Singapore, Singapore
Duration: Nov 18 1991Nov 21 1991

Publication series

Name91 IEEE Int Jt Conf Neural Networks IJCNN 91

Other

Other1991 IEEE International Joint Conference on Neural Networks - IJCNN '91
CitySingapore, Singapore
Period11/18/9111/21/91

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All Science Journal Classification (ASJC) codes

  • Engineering(all)

Cite this

Yang, J., & Honavar, V. (1991). Experiments with the cascade-correlation algorithm. In 91 IEEE Int Jt Conf Neural Networks IJCNN 91 (pp. 2428-2433). (91 IEEE Int Jt Conf Neural Networks IJCNN 91). Publ by IEEE.