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Table 4 Classification performance

From: Identifying tweets of personal health experience through word embedding and LSTM neural network

Classifier Accuracy Precision (PET) Recall (PET) F1 (PET) ROC/AUC
Logistic Regression 0.637 0.356 0.471 0.405 0.598
Decision Tree 0.602 0.329 0.442 0.357 0.547
KNN 0.669 0.383 0.481 0.411 0.604
SVM 0.635 0.339 0.478 0.393 0.580
BoW + Logistic Regr. 0.757 0.498 0.567 0.530 0.698
Word Embedding + LSTM 0.815 0.598 0.702 0.645 0.776
  1. The highest values are in boldface