Regression measure defined as $$ \frac{\sum_{i=1}^n \left| t_i - r_i \right|}{\sum_{i=1}^n \left| t_i - \bar{t} \right|}. $$ Can be interpreted as absolute error of the predictions relative to a naive model predicting the mean.

Note

The score function calls mlr3measures::rae() from package mlr3measures.

If the measure is undefined for the input, NaN is returned. This can be customized by setting the field na_value.

Dictionary

This Measure can be instantiated via the dictionary mlr_measures or with the associated sugar function msr():

mlr_measures$get("rae")
msr("rae")

Meta Information

  • Type: "regr"

  • Range: \([0, \infty)\)

  • Minimize: TRUE

  • Required prediction: response

See also