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A Study on Training Ensembles of Neural Networks - A Case of Stock Price Prediction
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Young-Chan Lee (Institute for Business Research, Sogang University)
Soo-Hwan Kwak (Graduate School of Business, Korea University)
Vol. 5, No. 1, Page: 95 ~ 101
Keywords
Neural Network, Generalization Performance, Overfitting, Bumping, Bumping, Balancing
Abstract
In this paper, a comparison between different methods to combine predictions from neural networks will be given. These methods are bagging, bumping, and balancing. Those are based on the analysis of the ensemble generalization error into an ambiguity term and a term incorporating generalization performances of individual networks. Neural Networks and AI machine learning models are prone to overfitting. A strategy to prevent a neural network from overfitting, is to stop training in early stage of the learning process. The complete data set is spilt up into a training set and a validation set. Training is stopped when the error on the validation set starts increasing. The stability of the networks is highly dependent on the division in training and validation set, and also on the random initial weights and the chosen minimization procedure. This causes early stopped networks to be rather unstable: a small change in the data or different initial conditions can produce large changes in the prediction. Therefore, it is advisable to apply the same procedure several times starting from different initial weights. This technique is often referred to as training ensembles of neural networks. In this paper, we presented a comparison of three statistical methods to prevent overfitting of neural network.
Show/Hide Detailed Information in Korean
신경망 학습앙상블에 관한 연구 - 주가예측을 중심으로 -
이영찬 (서강대학교)
곽수환 (고려대학교 경영대학원)
Cite this article
JIIS Style
Lee, Y.-C., and S.-H. Kwak, " A Study on Training Ensembles of Neural Networks - A Case of Stock Price Prediction ", Journal of Intelligence and Information Systems, Vol. 5, No. 1 (1999), 95~101.

IEEE Style
Young-Chan Lee, and Soo-Hwan Kwak, " A Study on Training Ensembles of Neural Networks - A Case of Stock Price Prediction ", Journal of Intelligence and Information Systems, vol. 5, no. 1, pp. 95~101, 1999.

ACM Style
Lee, Y.-C., and Kwak, S.-H., 1999. A Study on Training Ensembles of Neural Networks - A Case of Stock Price Prediction . Journal of Intelligence and Information Systems. 5, 1, 95--101.
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@article{Lee:JIIS:1999:74,
author = {Lee, Young-Chan and Kwak, Soo-Hwan},
title = { A Study on Training Ensembles of Neural Networks - A Case of Stock Price Prediction },
journal = {Journal of Intelligence and Information Systems},
issue_date = {June 1999},
volume = {5},
number = {1},
month = Jun,
year = {1999},
issn = {2288-4866},
pages = {95--101},
url = {},
doi = {},
publisher = {Korea Intelligent Information System Society},
address = {Seoul, Republic of Korea},
keywords = { Neural Network, Generalization Performance, Overfitting, Bumping, Bumping and Balancing },
}
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%A Soo-Hwan Kwak
%T A Study on Training Ensembles of Neural Networks - A Case of Stock Price Prediction
%J Journal of Intelligence and Information Systems
%@ 2288-4866
%V 5
%N 1
%P 95-101
%D 1999
%R
%I Korea Intelligent Information System Society