Abstract
Techniques to deal with the off diagonal elements in confusion matrices are proposed. They are tailored to detect problems of bias of classification among classes. A Bayesian approach is developed aiming to estimate overprediction and underprediction probabilities among classes.
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Barranco-Chamorro, I., Carrillo-García, R.M. (2023). Analysing Misclassifications in Confusion Matrices. In: Kitsos, C.P., Oliveira, T.A., Pierri, F., Restaino, M. (eds) Statistical Modelling and Risk Analysis. ICRA 2022. Springer Proceedings in Mathematics & Statistics, vol 430. Springer, Cham. https://doi.org/10.1007/978-3-031-39864-3_3
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