1. Davide Chicco and Giuseppe Jurman . 2020. The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation. BMC genomics 21, 1 ( 2020 ), 1–13. Davide Chicco and Giuseppe Jurman. 2020. The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation. BMC genomics 21, 1 (2020), 1–13.
2. Jacob Cohen . 1988. Statistical power analysis for the behavioral sciences Lawrence Earlbaum Associates . Routledge , New York, NY, USA . 20–26 pages. Jacob Cohen. 1988. Statistical power analysis for the behavioral sciences Lawrence Earlbaum Associates. Routledge, New York, NY, USA. 20–26 pages.
3. An introduction to ROC analysis
4. Empirical Comparison of Area under ROC curve (AUC) and Mathew Correlation Coefficient (MCC) for Evaluating Machine Learning Algorithms on Imbalanced Datasets for Binary Classification
5. Measuring classifier performance: a coherent alternative to the area under the ROC curve