COMPARISON OF THREE NEURAL NETWORK CLASSIFIERS FOR APHASIC AND NON-APHASIC NAMING DATA

Antti Järvelin

2008

Abstract

This paper reports a comparison of three neural network models (Multi-Layer Perceptrons, Probabilistic Neural Networks, Self-Organizing Maps) for classifying naming data of aphasic and non-aphasic speakers. The neural network classifiers were tested with the artificial naming data generated from confrontation naming data of 23 aphasic patients and one averaged control subjet. The results show that one node MLP neural network performed best in the classification task, while the two other classifiers performed typically 1 - 2 % worse than the MLP classifier. Although the differences between the different classifier types were small, these results suggests that a simple one node MLP classifier should be preferred over more complex neural network classifiers when classifying naming data of aphasic and non-aphasic speakers.

Paper Citation

in Harvard Style

Järvelin A. (2008). COMPARISON OF THREE NEURAL NETWORK CLASSIFIERS FOR APHASIC AND NON-APHASIC NAMING DATA . In Proceedings of the First International Conference on Health Informatics - Volume 2: HEALTHINF, (BIOSTEC 2008) ISBN 978-989-8111-16-6, pages 186-190. DOI: 10.5220/0001036701860190

in Bibtex Style

@conference{healthinf08,
author={Antti Järvelin},
title={COMPARISON OF THREE NEURAL NETWORK CLASSIFIERS FOR APHASIC AND NON-APHASIC NAMING DATA},
booktitle={Proceedings of the First International Conference on Health Informatics - Volume 2: HEALTHINF, (BIOSTEC 2008)},
year={2008},
pages={186-190},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001036701860190},
isbn={978-989-8111-16-6},
}

in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Health Informatics - Volume 2: HEALTHINF, (BIOSTEC 2008)
TI - COMPARISON OF THREE NEURAL NETWORK CLASSIFIERS FOR APHASIC AND NON-APHASIC NAMING DATA
SN - 978-989-8111-16-6
AU - Järvelin A.
PY - 2008
SP - 186
EP - 190
DO - 10.5220/0001036701860190