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A Comparison of MCC and CEN Error Measures in Multi-Class Prediction

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  • Giuseppe Jurman
  • Samantha Riccadonna
  • Cesare Furlanello

Abstract

We show that the Confusion Entropy, a measure of performance in multiclass problems has a strong (monotone) relation with the multiclass generalization of a classical metric, the Matthews Correlation Coefficient. Analytical results are provided for the limit cases of general no-information (n-face dice rolling) of the binary classification. Computational evidence supports the claim in the general case.

Suggested Citation

  • Giuseppe Jurman & Samantha Riccadonna & Cesare Furlanello, 2012. "A Comparison of MCC and CEN Error Measures in Multi-Class Prediction," PLOS ONE, Public Library of Science, vol. 7(8), pages 1-8, August.
    • Handle: RePEc:plo:pone00:0041882
    DOI: 10.1371/journal.pone.0041882
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    Cited by:

    1. Kong, Hyeongwoo & Yun, Wonje & Kim, Woo Chang, 2023. "Tracking customer risk aversion," Finance Research Letters, Elsevier, vol. 54(C).
    2. Van Quan Tran & Hai-Van Thi Mai & Thuy-Anh Nguyen & Hai-Bang Ly, 2021. "Investigation of ANN architecture for predicting the compressive strength of concrete containing GGBFS," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-21, December.
    3. Sankhadeep Chatterjee & Sarbartha Sarkar & Nilanjan Dey & Soumya Sen, 2018. "Non-Dominated Sorting Genetic Algorithm-II-Induced Neural-Supported Prediction of Water Quality with Stability Analysis," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 17(02), pages 1-20, June.
    4. Nader Salari & Shamarina Shohaimi & Farid Najafi & Meenakshii Nallappan & Isthrinayagy Karishnarajah, 2014. "A Novel Hybrid Classification Model of Genetic Algorithms, Modified k-Nearest Neighbor and Developed Backpropagation Neural Network," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-50, November.
    5. Bode, Gerrit & Thul, Simon & Baranski, Marc & Müller, Dirk, 2020. "Real-world application of machine-learning-based fault detection trained with experimental data," Energy, Elsevier, vol. 198(C).
    6. Yun Jiang & Li Chen & Hai Zhang & Xiao Xiao, 2019. "Breast cancer histopathological image classification using convolutional neural networks with small SE-ResNet module," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-21, March.

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