Using a Fuzzy Decision Tree Ensemble for Tumor Classification from Gene Expression Data

José M. Cadenas, M. Carmen Garrido, Raquel Martínez, David A. Pelta, Piero P. Bonissone

2013

Abstract

Machine learning techniques are useful tools that can help us in the knowledge extraction from gene expression data in biological systems. In this paper two machine learning techniques are applied to tumor datasets based on gene expression data. Both techniques are based on a fuzzy decision tree ensemble and are used to carry out the classification and selection of features on datasets. The classification accuracies obtained both when we use all genes to classify and when we only use the selected genes are high. However, in this second case the result also increases the interpretability of the solution provided by the technique. Additionally, the feature selection technique provides a ranking of importance of genes and a partitioning of the domains of the genes.

Paper Citation

in Harvard Style

Cadenas J., Garrido M., Martínez R., A. Pelta D. and P. Bonissone P. (2013). Using a Fuzzy Decision Tree Ensemble for Tumor Classification from Gene Expression Data . In Proceedings of the 5th International Joint Conference on Computational Intelligence - Volume 1: SCA, (IJCCI 2013) ISBN 978-989-8565-77-8, pages 320-331. DOI: 10.5220/0004658203200331

in Bibtex Style

@conference{sca13,
author={José M. Cadenas and M. Carmen Garrido and Raquel Martínez and David A. Pelta and Piero P. Bonissone},
title={Using a Fuzzy Decision Tree Ensemble for Tumor Classification from Gene Expression Data},
booktitle={Proceedings of the 5th International Joint Conference on Computational Intelligence - Volume 1: SCA, (IJCCI 2013)},
year={2013},
pages={320-331},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004658203200331},
isbn={978-989-8565-77-8},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Joint Conference on Computational Intelligence - Volume 1: SCA, (IJCCI 2013)
TI - Using a Fuzzy Decision Tree Ensemble for Tumor Classification from Gene Expression Data
SN - 978-989-8565-77-8
AU - Cadenas J.
AU - Garrido M.
AU - Martínez R.
AU - A. Pelta D.
AU - P. Bonissone P.
PY - 2013
SP - 320
EP - 331
DO - 10.5220/0004658203200331