rrse: Root Relative Squared Error

In Metrics: Evaluation Metrics for Machine Learning

Description

rrse computes the root relative squared error between two numeric vectors.

Usage

rrse(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.

Details

rrse takes the square root of sse(actual, predicted) divided by sse(actual, mean(actual)), meaning that it provides the squared error of the predictions relative to a naive model that predicted the mean for every data point.

See Also

rse rae

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)
rrse(actual, predicted)

Example output

[1] 0.2043785

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