Table 2:
Classification performance of the top performing ML models established after external validation for each of the four ML algorithms utilizing nine and ten features.
| Data set with nine features (without SDHB mutation status) | ||||
|---|---|---|---|---|
| Algorithms | TC | SVM | NB | ENS |
| AUC & CI | 0·889 (0·823-0.934) | 0·929 (0·889-0·957) | 0·839 (0·752-0·891) | 0·942 (0·894-0·969) |
| MCC | 0·863 (0·808-0·893) | 0.795 (0·735-0·840) | 0·710 (0·651-0·771) | 0·851 (0·801-0·898) |
| F1-score | 0·774 (0·699-0·863) | 0·661 (0·549-0·770) | 0·554 (0·417-0·610) | 0·755 (0·667-0·833) |
| Sensitivity | 0·854 (0·725-0·939) | 0·813 (0·687-0·909) | 0·854 (0·757-0·951) | 0·833 (0·707-0·929) |
| Specificity | 0·927 (0·894-0·957) | 0·866 (0·831-0·914) | 0·745 (0·690-0·808) | 0·922 (0·893-0·955) |
| Precision | 0·707 (0·599-0·841) | 0·557 (0·465-0·691) | 0·410 (0·308-0·506) | 0·690 (0·568-0·834) |
| Accuracy | 0·914 (0·879-0·939) | 0·857 (0·812-0·889) | 0·764 (0·723-0·805) | 0·907 (0·861-0·932) |
| Balanced Accuracy | 0·890 (0·822-0·933) | 0·839 (0·770-0·888) | 0·799 (0·758-0·840) | 0·878 (0·808-0·922) |
| Data set with ten features (with SDHB mutation status)* | ||||
| AUC & CI | 0·893 (0·823-0·936) | 0·924 (0·881-0·953) | 0.826 (0.751-0.878) | 0.940 (0.886-0.969) |
| MCC | 0·849 (0·782-0·891) | 0·795 (0·761-0·841) | 0·672 (0·617-0·719) | 0.804 (0·741-0·849) |
| F1-score | 0·750 (0·635-0·826) | 0.651 (0·533-0·726) | 0.559 (0·423-0·695) | 0·672 (0·571-0·780) |
| Sensitivity # | 0·750 (0·596-0·841) | 0·896 (0·783-0·962) | 0·791 (0·636-0·946) | 0·854 (0·777-0·939) |
| Specificity | 0·948 (0·908-0·974) | 0·821 (0·771-0·869) | 0·781 (0·726-0·836) | 0·859 (0·801-0·900) |
| Precision | 0·750 (0·578-0·834) | 0·512 (0·408-0·602) | 0·413 (0·293-0·546) | 0·554 (0·454-0·674) |
| Accuracy | 0·914 (0·877-0·942) | 0·834 (0·785-0·866) | 0·783 (0·749-0·832) | 0·856 (0·800-0·897) |
| Balanced Accuracy | 0·849 (0·793-0·910) | 0·858 (0·808-0·908) | 0·786 (0·752-0·820) | 0·855 (0.789-0·907) |
TC: Decision Tree Classifier, SVM: Support Vector Machine Classifier, NB: Naive Bayes Classifier, ENS: Ensemble Tree Classifiers, AUC: area under the Roc Curve; CI: 95% confidence intervals; MCC: Matthew`s correlation coefficient; #: sensitivity=recall rates; *Information regarding the presence or not of SDHB mutation was included as an extra feature