Description Usage Arguments Value Examples
View source: R/metric_recall.R
Returns the recall TP / (TP + FN) of a classification using the confusion matrix Note: Predictions should be annualized (independent of exposure) Note: Perfect recall is 1, poor model is 0
1 | metric_recall(actual, predicted, weight = NULL, na.rm = FALSE, threshold = 0.5)
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actual |
Array[Numeric] - Values we are aiming to predict. |
predicted |
Array[Numeric] - Values that we have predicted. |
weight |
Optional: Array[Numeric] - Weighting of predictions. If NULL even weighting is used |
na.rm |
Optional: boolean - If |
threshold |
Optional: Numeric between 0 and 1. If prediction proablity is below |
precision of classification TP / (TP + FN)
1 | metric_recall(actual=c(0,1,0,0), predicted=c(0.1,0.9,0.4,0.6))
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