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International Conference on Practical Applications of Computational Biology & Bioinformatics

PACBB2018 2018: Practical Applications of Computational Biology and Bioinformatics, 12th International Conference pp 200–207Cite as

A Genetic Programming Approach Applied to Feature Selection from Medical Data

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 803))

Abstract

Genetic programming represents a flexible and powerful evolutionary technique in machine learning. The use of genetic programming for rule induction has generated interesting results in classification problems. This paper proposes an evolutionary approach for logical rule induction, which is applied to clinical data. Since logical rules disclose knowledge from the analyzed data, we use such a knowledge to filter features from the target dataset. The results reached by the used dataset have been very promising when used in classification tasks and compared with other methods.

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Acknowledgments

This work has been carried out under the iCIS project (CENTRO-07-ST24-FEDER-002003), which has been co-financed by QREN, in the scope of the Mais Centro Program and European Union’s FEDER.

This work has also been partially supported by the Interreg V-A Spain-Portugal Program (PocTep) and the European Regional Development Fund (ERDF) under the IOTEC project (grant 0123_IOTEC_3_E).

The research of Juan Ramos González has been co-financed by the European Social Fund and Junta de Castilla y Len (Operational Programme 2014–2020 for Castilla y Len, BOCYL EDU/602/2016).

Author information

Authors and Affiliations

  1. IBSAL/BISITE Research Group, Edificio I+D+i USAL, University of Salamanca, C/ Espejo s/n, 37007, Salamanca, Spain

    José A. Castellanos-Garzón, Juan Ramos, Yeray Mezquita Martín & Juan F. de Paz

  2. CISUC, ECOS Research Group, Pólo II - Pinhal de Marrocos, University of Coimbra, 3030-290, Coimbra, Portugal

    José A. Castellanos-Garzón & Ernesto Costa

Authors
  1. José A. Castellanos-Garzón
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  2. Juan Ramos
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  3. Yeray Mezquita Martín
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  4. Juan F. de Paz
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  5. Ernesto Costa
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Corresponding author

Correspondence to José A. Castellanos-Garzón .

Editor information

Editors and Affiliations

  1. Escuela Superior de Ingeniería Informática, Universidad de Vigo, Ourense, Spain

    Florentino Fdez-Riverola

  2. Faculty of Computing, Department of Software Engineering, Universiti Teknologi Malaysia, Johor, Malaysia

    Mohd Saberi Mohamad

  3. Department de Informática, Universidade do Minho, Braga, Portugal

    Miguel Rocha

  4. Departamento de Informática y Automática, Facultad de Ciencias, Universidad de Salamanca, Salamanca, Spain

    Juan F. De Paz

  5. Departamento de Sistemas Informáticos, Universidad de Castilla-La Mancha, Albacete, Albacete, Spain

    Pascual González

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Castellanos-Garzón, J.A., Ramos, J., Martín, Y.M., de Paz, J.F., Costa, E. (2019). A Genetic Programming Approach Applied to Feature Selection from Medical Data. In: Fdez-Riverola, F., Mohamad, M., Rocha, M., De Paz, J., González, P. (eds) Practical Applications of Computational Biology and Bioinformatics, 12th International Conference. PACBB2018 2018. Advances in Intelligent Systems and Computing, vol 803. Springer, Cham. https://doi.org/10.1007/978-3-319-98702-6_24

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