Stability Evaluation of Combined Neural Networks

Ibtissem Ben Othman, Faouzi Ghorbel


In the industrial field, the artificial neural network classifiers are currently used and they are generally integrated of technologic systems which need efficient classifier. However, the lack of control over its mathematical formulation explains the instability of its classification results. In order to improve the prediction accuracy, most of researchers refer to the classifiers combination approach. This paper tries to illustrate the capability of an example of combined neural networks to improve the stability criterion of the single neural classifier. The stability comparison is performed by the error rate probability densities function estimated by a new variant of the kernel-diffeomorphism semi-bounded Plug-in algorithm.


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Paper Citation

in Harvard Style

Ben Othman I. and Ghorbel F. (2014). Stability Evaluation of Combined Neural Networks . In Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2014) ISBN 978-989-758-054-3, pages 203-209. DOI: 10.5220/0005077402030209

in Bibtex Style

author={Ibtissem Ben Othman and Faouzi Ghorbel},
title={Stability Evaluation of Combined Neural Networks},
booktitle={Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2014)},

in EndNote Style

JO - Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2014)
TI - Stability Evaluation of Combined Neural Networks
SN - 978-989-758-054-3
AU - Ben Othman I.
AU - Ghorbel F.
PY - 2014
SP - 203
EP - 209
DO - 10.5220/0005077402030209