recall: Recall

In Metrics: Evaluation Metrics for Machine Learning

Description

recall computes proportion of observations in the positive class (i.e. the element in actual equals 1) that are predicted to be in the positive class (i.e. the element in predicted equals 1)

Usage

recall(actual, predicted)

Arguments

actual	The ground truth binary numeric vector containing 1 for the positive class and 0 for the negative class.
predicted	The predicted binary numeric vector containing 1 for the positive class and 0 for the negative class. Each element represents the prediction for the corresponding element in actual.

See Also

precision fbeta_score

Examples

actual <- c(1, 1, 1, 0, 0, 0)
predicted <- c(1, 0, 1, 1, 1, 1)
recall(actual, predicted)

Example output

[1] 0.6666667

Metrics documentation built on May 1, 2019, 10:11 p.m.