This function calculates the recall (also known as sensitivity) of a model based on the provided metrics and the true target values. Recall is defined as the ratio of true positive predictions to all actual positive instances (true positives + false negatives).
Arguments
- metrics
A data frame with metrics obtained using
get_sensitivity_specificity(), containing at least two columns: "Sensitivity" and "Specificity".- target
A character vector containing the true values from the target variable. It should have the same length as the predictions.