This function lets the user get a confusion matrix and accuracy, and for for binary classification models: AUC, Precision, Sensitivity, and Specificity.
mmetrics(tag, score, thresh = 0.5, plot = FALSE, size = 2.5,
roc = FALSE)Vector. Real known label
Vector. Predicted value or model's result
Numeric. Value which splits the results for the confusion matrix.
Boolean. Plot a Confusion Matrix graph?
Numeric. Change bubble's size if needed
Boolean. Plot ROC Curce with AUC?