precision: Precision

In Metrics: Evaluation Metrics for Machine Learning

Description

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

Usage

precision(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

recall fbeta_score

Examples

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

Example output

[1] 0.5

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