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Table 3 Comparison of machine learning approaches

From: Prediction of incident myocardial infarction using machine learning applied to harmonized electronic health record data

  F1 Score AUC Training time
Naïve Bayes 0.060 0.73 1 min
Logistic regression with L2 regularization 0.084 0.829 1 min
Logstic regression with no regularization 0.06 0.79 1 min
RF 0.084 0.765 3 min
Shallow NN 0.101 0.83 1 min
Deep NN 0.092 0.835 2 min
GBM 0.077 0.83 9 min
  1. Comparison of various models using Random Undersampling technique and all features. F1 and AUC calculated from model applied to held-out testing set (20%); training time is for training of training set (80%)