metric_recall: metric_recall

Description Usage Arguments Value Examples

View source: R/metric_recall.R

Description

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

Usage

1
metric_recall(actual, predicted, weight = NULL, na.rm = FALSE, threshold = 0.5)

Arguments

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 FALSE function will return NA is any value in NA

threshold

Optional: Numeric between 0 and 1. If prediction proablity is below threshold the predicted value is 0.

Value

precision of classification TP / (TP + FN)

Examples

1
metric_recall(actual=c(0,1,0,0), predicted=c(0.1,0.9,0.4,0.6))

gloverd2/admr documentation built on Dec. 2, 2020, 11:16 p.m.