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Learning Optimal Decision Lists as a Metaheuristic Search for Diagnosis of Parkinson’s Disease

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Machine Learning, Optimization, and Big Data (MOD 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10122))

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Abstract

Decision Lists are a very general model representation. In learning decision structures from medical datasets one needs a simple understandable model. Such a model should correctly classify unknown cases. One must search for the most general decision structure using the training dataset as input, taking into account both complexity and goodness-of-fit of the underlying model. In this paper, we propose to search the Decision List state space as an optimization problem using a metaheuristic. We implemented the method and carried out experimentation over a well-known Parkinson’s Disease training set. Our results are encouraging when compared to other machine learning references on the same dataset.

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Authors and Affiliations

  1. Computer Science Department and Virtual University Institute, Federal University of Ceará, Campus do Pici, Bloco 952, Fortaleza, Ceará, 60455, Brazil

    Fernando de Carvalho Gomes & José Gilvan Rodrigues Maia

Authors
  1. Fernando de Carvalho Gomes
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  2. José Gilvan Rodrigues Maia
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Corresponding author

Correspondence to Fernando de Carvalho Gomes .

Editor information

Editors and Affiliations

  1. Department of Industrial and Systems Engineering, University of Florida, Gainesville, Florida, USA

    Panos M. Pardalos

  2. Semantic Technology Laboratory, National Research Council (CNR), Catania, Italy

    Piero Conca

  3. Dipartimento di Sociologia e Metodi della Ricerca Sociale, Università di Catania, Catania, Italy

    Giovanni Giuffrida

  4. Department of Mathematics and Computer Science, University of Catania, Catania, Italy

    Giuseppe Nicosia

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de Carvalho Gomes, F., Maia, J.G.R. (2016). Learning Optimal Decision Lists as a Metaheuristic Search for Diagnosis of Parkinson’s Disease. In: Pardalos, P., Conca, P., Giuffrida, G., Nicosia, G. (eds) Machine Learning, Optimization, and Big Data. MOD 2016. Lecture Notes in Computer Science(), vol 10122. Springer, Cham. https://doi.org/10.1007/978-3-319-51469-7_32

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  • DOI: https://doi.org/10.1007/978-3-319-51469-7_32

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-51468-0

  • Online ISBN: 978-3-319-51469-7

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