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Table 3 The AUC comparison between LR and other models in testing dataset

From: A nomogram to distinguish noncardiac chest pain based on cardiopulmonary exercise testing in cardiology clinic

Models

ΔAUC

95%CI

Z statistic

P value

LR ∼ XGBoost

0.051

0.019,0.083

3.152

0.002

LR ∼ RF

0.023

-0.001,0.047

1.914

0.056

LR ∼ Bagtree

0.058

0.026,0.089

3.581

< 0.001

LR ∼ SVM

0.048

0.012,0.085

2.595

0.009

LR ∼ LDA

-0.002

-0.008,0.003

-0.843

0.399

LR ∼ Decision Tree

0.030

-0.005,0.064

1.703

0.089

LR ∼ Naive Bayes

0.048

0.023,0.073

3.748

< 0.001

  1. LR: Logistic Regression; XGBoost: Extreme Gradient Boosting; RF: Random Forest; Bagtree: Bagged Trees; SVM: Support Vector Machine; LDA: Linear Discriminant Analysis; AUC: area under the receiver operating characteristic curve; ΔAUC: the difference of AUC between two models
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BMC Medical Informatics and Decision Making

ISSN: 1472-6947

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