| auc | Area Under the Curve |
| auc.default | Area Under the Curve |
| auc.gbm | Area Under the Curve |
| auc.glm | Area Under the Curve |
| auc.glmerMod | Area Under the Curve |
| auc.randomForest | Area Under the Curve |
| auc.rpart | Area Under the Curve |
| brier | Brier Score |
| brier.default | Brier Score |
| brier.gbm | Brier Score |
| brier.glm | Brier Score |
| brier.glmerMod | Brier Score |
| brier.randomForest | Brier Score |
| brier.rpart | Brier Score |
| ce | Classification error |
| ce.default | Classification error |
| ce.gbm | Classification error |
| ce.glm | Classification error |
| ce.glmerMod | Classification error |
| ce.lm | Classification error |
| ce.randomForest | Classification error |
| ce.rpart | Classification error |
| confusionMatrix | Confusion Matrix |
| f1Score | F1 Score |
| fScore | F Score |
| gini | GINI Coefficient |
| gini.default | GINI Coefficient |
| gini.gbm | GINI Coefficient |
| gini.glm | GINI Coefficient |
| gini.glmerMod | GINI Coefficient |
| gini.randomForest | GINI Coefficient |
| gini.rpart | GINI Coefficient |
| kappa | kappa statistic |
| logLoss | Log Loss |
| logLoss.default | Log Loss |
| logLoss.gbm | Log Loss |
| logLoss.glm | Log Loss |
| logLoss.glmerMod | Log Loss |
| logLoss.randomForest | Log Loss |
| logLoss.rpart | Log Loss |
| mae | Mean absolute error |
| mae.default | Mean absolute error |
| mae.gbm | Mean absolute error |
| mae.glm | Mean absolute error |
| mae.glmerMod | Mean absolute error |
| mae.randomForest | Mean absolute error |
| mae.rpart | Mean absolute error |
| mauc | Multiclass Area Under the Curve |
| mcc | Matthews Correlation Coefficient |
| mlogLoss | Multiclass Log Loss |
| mse | Mean Square Error |
| mse.default | Mean Square Error |
| mse.glm | Mean Square Error |
| mse.lm | Mean Square Error |
| msle | Mean Squared Log Error |
| msle.default | Mean Squared Log Error |
| msle.gbm | Mean Squared Log Error |
| msle.glm | Mean Squared Log Error |
| msle.glmerMod | Mean Squared Log Error |
| msle.lm | Mean Squared Log Error |
| msle.randomForest | Mean Squared Log Error |
| msle.rpart | Mean Squared Log Error |
| npv | Negative Predictive Value |
| ppv | Positive Predictive Value |
| precision | Positive Predictive Value |
| recall | Recall, Sensitivity, tpr |
| rmse | Root-Mean Square Error |
| rmse.default | Root-Mean Square Error |
| rmse.glm | Root-Mean Square Error |
| rmse.lm | Root-Mean Square Error |
| rmsle | Root Mean Squared Log Error |
| rmsle.default | Root Mean Squared Log Error |
| rmsle.gbm | Root Mean Squared Log Error |
| rmsle.glm | Root Mean Squared Log Error |
| rmsle.glmerMod | Root Mean Squared Log Error |
| rmsle.lm | Root Mean Squared Log Error |
| rmsle.randomForest | Root Mean Squared Log Error |
| rmsle.rpart | Root Mean Squared Log Error |
| sensitivity | Recall, Sensitivity, tpr |
| specificity | Specificity, True negative rate |
| testDF | Test data |
| tnr | Specificity, True negative rate |
| tpr | Recall, Sensitivity, tpr |