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Table 11 Comparison between the training variable set and the external variable set

From: Predicting postoperative complications of head and neck squamous cell carcinoma in elderly patients using random forest algorithm model

Variable set (Training)

CA (Accuracy, %)

AUC

All Random Forest

89.084 %

0.949

All Rotation Forest

85.965 %

0.942

All SVM

83.431 %

0.930

All Bayesian Network

82.261 %

0.905

All Naïve Bayesian Network

75.634 %

0.865

Variable set (external)

  

All Random Forest

83.333 %

0.781

  1. All “All Variable” system
  2. SVM support vector machine
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BMC Medical Informatics and Decision Making

ISSN: 1472-6947

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