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. 2023 Jun 2;13:8989. doi: 10.1038/s41598-023-36172-7

Table 10.

Results for Rather absent Tinnitus Users (downsampled), including standard deviation.

Rather absent Tinnitus Users down
Accuracy F1-score AUC Precision Sensitivity Specificity
DT 0.657 (+/− 0.006) 0.661 (+/− 0.008) 0.662 (+/− 0.007) 0.653 (+/− 0.008) 0.669 (+/− 0.017) 0.644 (+/− 0.017)
RFC 0.683 (+/− 0.010) 0.687 (+/− 0.011) 0.753 (+/− 0.012) 0.678 (+/− 0.011) 0.697 (+/− 0.015) 0.669 (+/− 0.015)
SVM 0.620 (+/− 0.012) 0.590 (+/− 0.013) 0.659 (+/− 0.013) 0.641 (+/− 0.016) 0.547 (+/− 0.014) 0.693 (+/− 0.018)
CNB 0.595 (+/− 0.010) 0.578 (+/− 0.012) 0.616 (+/− 0.012) 0.603 (+/− 0.011) 0.556 (+/− 0.016) 0.635 (+/− 0.017)
KNC 0.651 (+/− 0.010) 0.652 (+/− 0.010) 0.703 (+/− 0.011) 0.650 (+/− 0.011) 0.655 (+/− 0.012) 0.647 (+/− 0.015)
LRC 0.601 (+/− 0.012) 0.605 (+/− 0.013) 0.632 (+/− 0.016) 0.600 (+/− 0.012) 0.610 (+/− 0.016) 0.592 (+/− 0.015)
MLP 0.648 (+/− 0.009) 0.633 (+/− 0.017) 0.704 (+/− 0.011) 0.663 (+/− 0.018) 0.607 (+/− 0.041) 0.690 (+/− 0.043)
XGB 0.672 (+/− 0.010) 0.664 (+/− 0.011) 0.739 (+/− 0.011) 0.681 (+/− 0.010) 0.649 (+/− 0.013) 0.696 (+/− 0.010)

Decision Tree (DT), Random Forest (RFC), Support Vector Machine (SVM), Complement Naive Bayes (CNB), k-nearest neighbors (KNC), Logistic Regression (LRC), Multi-layer Perceptron (MLP), Extreme Gradient Boosting (XGB)

Highest values are in bold.