ae: Absolute Error

In Metrics: Evaluation Metrics for Machine Learning

Description

ae computes the elementwise absolute difference between two numeric vectors.

Usage

ae(actual, predicted)

Arguments

actual	The ground truth numeric vector.
predicted	The predicted numeric vector, where each element in the vector is a prediction for the corresponding element in actual.

See Also

mae mdae mape

Examples

actual <- c(1.1, 1.9, 3.0, 4.4, 5.0, 5.6)
predicted <- c(0.9, 1.8, 2.5, 4.5, 5.0, 6.2)
ae(actual, predicted)

Example output

[1] 0.2 0.1 0.5 0.1 0.0 0.6

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