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Table 2 The AUC values and other performance metrics for the four machine learning algorithms

From: Predicting autoimmune thyroiditis in primary Sjogren’s syndrome patients using a random forest classifier: a retrospective study

Metric

ROC

ACC

PPV

NPV

SENS

SEPC

F1

LR

0.552

0.55

0.57

0.53

0.53

0.57

0.55

XGB

0.652

0.66

0.65

0.67

0.73

0.57

0.66

SVM

0.690

0.69

0.71

0.67

0.67

0.71

0.69

RFC

0.755

0.77

0.72

0.82

0.87

0.64

0.75

  1. Remarks: LR Logistic Regression, XGB Extreme Gradient Boosting, SVM Support Vector Machine, RFC Random Forest Classifier, ROC receiver operator characteristic curve, ACC accuracy, PPV positive predictive value, NPV negative predictive value, SENS sensitivity, SEPC specificity
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Arthritis Research & Therapy

ISSN: 1478-6362

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