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Authors: Seiya Satoh 1 and Ryohei Nakano 2

Affiliations: 1 National Institute of Advanced Industrial Science and Tech, Japan ; 2 Chubu University, Japan

Keyword(s): Information Criteria, Model Selection, Multilayer Perceptron, Singular Model.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Methodologies and Methods ; Model Selection ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Regression ; Sensor Networks ; Signal Processing ; Soft Computing ; Theory and Methods

Abstract: The present paper evaluates newly invented information criteria for singular models. Well-known criteria such as AIC and BIC are valid for regular statistical models, but their validness for singular models is not guaranteed. Statistical models such as multilayer perceptrons (MLPs), RBFs, HMMs are singular models. Recently WAIC and WBIC have been proposed as new information criteria for singular models. They are developed on a strict mathematical basis, and need empirical evaluation. This paper experimentally evaluates how WAIC and WBIC work for MLP model selection using conventional and new learning methods.

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Paper citation in several formats:
Satoh, S. and Nakano, R. (2017). How New Information Criteria WAIC and WBIC Worked for MLP Model Selection. In Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-222-6; ISSN 2184-4313, SciTePress, pages 105-111. DOI: 10.5220/0006120301050111

@conference{icpram17,
author={Seiya Satoh. and Ryohei Nakano.},
title={How New Information Criteria WAIC and WBIC Worked for MLP Model Selection},
booktitle={Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2017},
pages={105-111},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006120301050111},
isbn={978-989-758-222-6},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - How New Information Criteria WAIC and WBIC Worked for MLP Model Selection
SN - 978-989-758-222-6
IS - 2184-4313
AU - Satoh, S.
AU - Nakano, R.
PY - 2017
SP - 105
EP - 111
DO - 10.5220/0006120301050111
PB - SciTePress