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

نویسندگان

  • Giuseppe Jurman
  • Samantha Riccadonna
  • Cesare Furlanello
چکیده

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.

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عنوان ژورنال:

دوره 7  شماره 

صفحات  -

تاریخ انتشار 2012