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Enhancing Confusion Entropy as Measure for Evaluating Classifiers

  • Rosario Delgado
  • J. David Núñez-GonzálezEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 771)

Abstract

Performance measures are used in Machine Learning to assess the behaviour of classifiers. Many measures have been defined on the literature. In this work we focus on Confusion Entropy (CEN), a measure based in Shannon’s Entropy. We introduce a modification of this measure that overcomes its disadvantages in the binary case that disables it as a suitable measure to compare classifiers. We compare this modification with CEN and other measures, presenting analytical results in some particularly interesting cases, as well as some heuristic computational experimentation.

Keywords

Classifier Performance measure Confusion Entropy (CEN) 

Notes

Acknowledgements

This work have been supported by Ministerio de Economía y Competitividad, Gobierno de España, project ref. MTM2015 67802-P.

References

  1. 1.
    Antunes, F., Ribeiro, B., Pereira, F.: Probabilistic modeling and visualization for bankruptcy prediction. Appl. Soft Comput. 60, 831–843 (2017)CrossRefGoogle Scholar
  2. 2.
    Jin, H., Wang, X.-N., Gao, F., Li, J., Wei, J.-M.: Learning Decision Trees using Confusion Entropy. Proceedings of the 2013 International Conference on Machine Learning and Cybernetics, Tianjin, 14–17 July (2013)Google Scholar
  3. 3.
    Jurman, G., Riccadonna, S., Furlanello, C.: A comparison of MCC and CEN error measures in multi-class prediction. Plos One 7(8), 1–8 (2012)CrossRefGoogle Scholar
  4. 4.
    Lichman, M.: UCI Machine Learning Repository. University of California, Irvine, School of Information and Computer Sciences (2013). https://archive.ics.uci.edu/ml/index.php
  5. 5.
    Marques de S., J.-P., Bernardes, J., Ayres de Campos, D.: UCI Machine Learning Repository: Cardiotocography Data Set (2010)Google Scholar
  6. 6.
    Matthews, B.: Comparison of the predicted and observed secondary structure of T4 phage lysozyme. Biochimica et biophysica acta. Vol 405, Num 2, 442–451 (1975)CrossRefGoogle Scholar
  7. 7.
    Roumani, Y.-F., May, J.-H., Strum, D.-P.: Classifying highly imbalanced ICU data. Health Care Manag. Sci. 16, 119–128 (2013)CrossRefGoogle Scholar
  8. 8.
    Roumani, Y.-F., Rouman, Y., Nwankpa, J.-K., Tanniru, M.: Classifying readmissions to a cardiac intensive care unit. Ann. Oper. Res. 263(1–2), 429–451 (2018)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Sherman, I.-B.: On the Role of Genetic Algorithms in the Pattern Recognition Task of Classification. Master’s Thesis, University of Tennessee, 2017. http://trace.tennessee.edu/utk_gradthes/4780
  10. 10.
    Sublime, J., Grozavu, N., Cabanes, G., Bennani, Y., Cornuéjols, A.: From Horizontal to Vertical Collaborative Clustering using Generative Topographic Maps. International Journal of Hybrid Intelligent Systems, vol. 12(4), 245–256 (2015).  https://doi.org/10.3233/HIS-160219CrossRefGoogle Scholar
  11. 11.
    Sublime, J., Matei, B., Murena, P.-A.: Analysis of the influence of diversity in collaborative and multi-view clustering. In: 2017 International Joint Conference on Neural Networks (IJCNN), Anchorage, AK, 4126–4133 (2017).  https://doi.org/10.1109/IJCNN.2017.7966377
  12. 12.
    Sublime, J., Matei, B., Cabanes, G., Grozavu, N., Bennani, Y., Cornuéjols, A.: Entropy based probabilistic collaborative clustering. Pattern Recogn. 72, 144–157 (2017)CrossRefGoogle Scholar
  13. 13.
    Wang, X.-N., Wei, J.-M., Jin, H., Yu, G., Zhang, H.-W.: Probabilistic Confusion Entropy for Evaluating Classifiers. Entropy 15, 4969–4992 (2013)MathSciNetCrossRefGoogle Scholar
  14. 14.
    Wei, J.-M., Yuan, X.-Y., Hu, Q.-H., Wang, S.-Q.: A novel measure for evaluating classifiers. Expert Syst. Appl. 37, 3799–3809 (2010)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of MathematicsUniversitat Autònoma de BarcelonaCerdanyola del VallèsSpain
  2. 2.Department of MathematicsUniversity of the Basque Country (UPV/EHU)LeioaSpain

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