ures/results/crit_diff_uncal_classifiers_acc "fig:"){width="\linewidth"}

[.49]{} ![Critical difference of uncalibrated classifiers.[]{data-label="fig:uncal:cd:all"}](figures/results/crit_diff_uncal_classifiers_loss "fig:"){width="\linewidth"}

[.49]{} ![Critical difference of uncalibrated classifiers.[]{data-label="fig:uncal:cd:all"}](figures/results/crit_diff_uncal_classifiers_brier "fig:"){width="\linewidth"}

[.49]{} ![Critical difference of uncalibrated classifiers.[]{data-label="fig:uncal:cd:all"}](figures/results/crit_diff_uncal_classifiers_mce "fig:"){width="\linewidth"}

[.49]{} ![Critical difference of uncalibrated classifiers.[]{data-label="fig:uncal:cd:all"}](figures/results/crit_diff_uncal_classifiers_conf-ece "fig:"){width="\linewidth"}

[.49]{} ![Critical difference of uncalibrated classifiers.[]{data-label="fig:uncal:cd:all"}](figures/results/crit_diff_uncal_classifiers_cw-ece "fig:"){width="\linewidth"}

[.49]{} ![Critical difference of uncalibrated classifiers.[]{data-label="fig:uncal:cd:all"}](figures/results/crit_diff_uncal_classifiers_p-conf-ece "fig:"){width="\linewidth"}

[.49]{} ![Critical difference of uncalibrated classifiers.[]{data-label="fig:uncal:cd:all"}](figures/results/crit_diff_uncal_classifiers_p-cw-ece "fig:"){width="\linewidth"}

Figure \[fig:uncal:cd:all\] shows the Critical Difference diagram for all the $8$ metrics. In particular, the MLP and the SVC with linear kernel are always in the group with the higher rankings and never in the lowest. Similarly, random forest is consistently in the best group, but in the worst group as well in $4$ of the measures. SVC with radial basis kernel is in the best group $6$ times, but $3$ times in the worst. On the other hand, naive Bayes and Adaboost SAMME are consistently in the worst group and never in the best one. The rest of the classifiers did not show a clear ranking position.

[.4]{} ![Proportion of times each classifier is already calibrated with different p-tests.[]{data-label="fig:uncal:p:ece"}](figures/results/p_table_classifie