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Authors: José M. Cadenas 1 ; M. Carmen Garrido 1 ; Raquel Martínez 1 ; David A. Pelta 2 and Piero P. Bonissone 3

Affiliations: 1 Computer Faculty and University of Murcia, Spain ; 2 University of Granada, Spain ; 3 General Electric Global Research, United States

Keyword(s): Fuzzy Random Forest, Gene Selection, Gene Expression Data, Tumor Datasets.

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.

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Paper citation in several formats:
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 (IJCCI 2013) - SCA; ISBN 978-989-8565-77-8; ISSN 2184-3236, SciTePress, pages 320-331. DOI: 10.5220/0004658203200331

@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 (IJCCI 2013) - SCA},
year={2013},
pages={320-331},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004658203200331},
isbn={978-989-8565-77-8},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 5th International Joint Conference on Computational Intelligence (IJCCI 2013) - SCA
TI - Using a Fuzzy Decision Tree Ensemble for Tumor Classification from Gene Expression Data
SN - 978-989-8565-77-8
IS - 2184-3236
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
PB - SciTePress

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