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ILIOU machine learning preprocessing method for depression type prediction

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Abstract

The main objective of this study was to find a data preprocessing method to boost the prediction performance of the machine learning algorithms in datasets of mental patients. Specifically, the machine learning methods must have almost excellent classification results in patients with depression, in order to achieve the sooner the possible the appropriate treatment. In this paper, we establish ILIOU data preprocessing method for Depression type detection. The performance of ILIOU data preprocessing method and principal component analysis preprocessing method was evaluated using the tenfold cross validation method assessing seven machine learning classification algorithms, nearest-neighbour classifier (IB1), C4.5 algorithm implementation (J48), random forest, multilayer perceptron (MLP), support vector machine (SMO), JRIP and fuzzy logic (FURIA), respectively. The classification results are presented and compared analytically. The experimental results reveal that the transformed dataset with new features after ILIOU preprocessing method implementation to the original dataset achieved 100% classification–prediction performance of the classification algorithms. So ILIOU data preprocessing method can be used for significantly boost classification algorithms performance in similar datasets and can be used for depression type prediction.

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Authors and Affiliations

  1. Medical Informatics Laboratory, Medical School, Democritus University of Thrace, Thrace, Greece

    Theodoros Iliou, Christina Lymperopoulou, Dimitrios Galiatsatos & George Anastassopoulos

  2. Special Office for Health Consulting Services, University of Patras, Patras, Greece

    Georgia Konstantopoulou

  3. Wire Communications Laboratory, Department of Electrical Engineering, University of Patras, Patras, Greece

    Mandani Ntekouli

  4. Department of Psychiatry, University of Patras, Patras, Greece

    Konstantinos Assimakopoulos

Authors
  1. Theodoros Iliou
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  2. Georgia Konstantopoulou
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  3. Mandani Ntekouli
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  4. Christina Lymperopoulou
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  5. Konstantinos Assimakopoulos
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  6. Dimitrios Galiatsatos
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  7. George Anastassopoulos
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Corresponding author

Correspondence to George Anastassopoulos.

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Iliou, T., Konstantopoulou, G., Ntekouli, M. et al. ILIOU machine learning preprocessing method for depression type prediction. Evolving Systems 10, 29–39 (2019). https://doi.org/10.1007/s12530-017-9205-9

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  • DOI: https://doi.org/10.1007/s12530-017-9205-9

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