Table 3 Learning algorithms and their default settings.
From: Predictive modeling of structured electronic health records for adverse drug event detection
Classifier | Description | Notes |
|---|---|---|
DT | CART decision tree | minimum 1 instance per leaf |
SVM Poly | Support Vector Machine | polynomial kernel of degree 3 |
SVM RBF | Support Vector Machine | RBF kernel, gamma = 0.0 |
LogReg | Logistic Regression | L2 regularization |
kNN | k nearest neighbors | k = 5 |
AdaBoost | Adaptive boosting | Decision trees, 50 base estimators |
Bagging | Bagging using CART tree | 10 base estimators |
NB | Naïve Bayes | |
RF | Random forest | 500 trees, inspected features = |