Table 2.
Results of models predicting the success of rest defending situations (successful/unsuccessful rest defense).
Classifier
Number of features
Accuracy
Precision
f1-Score
AUC
Logistic regression (ridge regression regularization)
17
0.87
0.56
0.57
0.76
Logistic regression (elastic net regularization)
17
0.82
0.54
0.54
0.74
Random Forest Classifier
17
0.84
0.55
0.56
0.78
Gradient Boosting
17
0.97
0.48
0.49
0.50
XGBoost Classifier
17
0.92
0.59
0.62
0.75
AdaBoost Classifier
17
0.96
0.63
0.61
0.60
AdaBoost Classifier (excluding distance variables)
15
0.97
0.73
0.64
0.60