GEML: Evolutionary Unsupervised and Semi-Supervised Learning of Multi-class Classification with Grammatical Evolution
Jeannie M. Fitzgerald, R. Mohammed Atif Azad, Conor Ryan
2015
Abstract
This paper introduces a novel evolutionary approach which can be applied to supervised, semi-supervised and unsupervised learning tasks. The method, Grammatical Evolution Machine Learning (GEML) adapts machine learning concepts from decision tree learning and clustering methods, and integrates these into a Grammatical Evolution framework. With minor adaptations to the objective function the system can be trivially modified to work with the conceptually different paradigms of supervised, semi-supervised and unsupervised learning. The framework generates human readable solutions which explain the mechanics behind the classification decisions, offering a significant advantage over existing paradigms for unsupervised and semi-supervised learning. GEML is studied on a range of multi-class classification problems and is shown to be competitive with several state of the art multi-class classification algorithms.
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Paper Citation
in Harvard Style
M. Fitzgerald J., Azad R. and Ryan C. (2015). GEML: Evolutionary Unsupervised and Semi-Supervised Learning of Multi-class Classification with Grammatical Evolution . In Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 1: ECTA, ISBN 978-989-758-157-1, pages 83-94. DOI: 10.5220/0005599000830094
in Bibtex Style
@conference{ecta15,
author={Jeannie M. Fitzgerald and R. Mohammed Atif Azad and Conor Ryan},
title={GEML: Evolutionary Unsupervised and Semi-Supervised Learning of Multi-class Classification with Grammatical Evolution},
booktitle={Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 1: ECTA,},
year={2015},
pages={83-94},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005599000830094},
isbn={978-989-758-157-1},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 1: ECTA,
TI - GEML: Evolutionary Unsupervised and Semi-Supervised Learning of Multi-class Classification with Grammatical Evolution
SN - 978-989-758-157-1
AU - M. Fitzgerald J.
AU - Azad R.
AU - Ryan C.
PY - 2015
SP - 83
EP - 94
DO - 10.5220/0005599000830094