@inproceedings{d69ce43f7936429b981031198bbb1a52,
title = "Prediction capability of neural networks trained by Monte-Carlo paradigm",
abstract = "The Monte-Carlo training paradigm for Artificial Neural Networks has been studied, the training short cut to reduce the training time has been discussed, and the prediction capability of such a trained neural network has been compared with the prediction capability of a neural net trained by the Backpropagation paradigm and with the statistical approach of the Discriminant Analysis. The Artificial Neural Network trained by the Monte-Carlo method proves itself as a reliable prediction tool which is superior to Discriminant Analysis and the Backpropagation training paradigm.",
keywords = "Intelligent systems, Machine learning, Neural netwok",
author = "Hashemi, {Ray R.} and Chowdhury, {Aslam H.} and Stafford, {Nancy L.} and Talburt, {John R.}",
note = "Publisher Copyright: {\textcopyright} 1993 ACM.; 1993 ACM/SIGAPP Symposium on Applied Computing: States of the Art and Practice, SAC 1993 ; Conference date: 14-02-1993 Through 16-02-1993",
year = "1993",
month = mar,
day = "1",
doi = "10.1145/162754.162763",
language = "English",
series = "Proceedings of the ACM Symposium on Applied Computing",
publisher = "Association for Computing Machinery",
pages = "9--13",
editor = "Ed Deaton and George Hedrick and K.M. George and Hal Berghel",
booktitle = "Proceedings of the 1993 ACM/SIGAPP Symposium on Applied Computing",
address = "United States",
}