rse: Relative Squared Error

In Metrics: Evaluation Metrics for Machine Learning

Description

rse computes the relative squared error between two numeric vectors.

Usage

rse(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

rse divides sse(actual, predicted) 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

rrse 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)
rse(actual, predicted)

Example output

[1] 0.04177057

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