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.
This Measure can be instantiated via the dictionary mlr_measures or with the associated sugar function msr():
mlr_measures$get("rae")
msr("rae")
Type: "regr"
Range: \([0, \infty)\)
Minimize: TRUE
Required prediction: response
Dictionary of Measures: mlr_measures
as.data.table(mlr_measures) for a complete table of all (also dynamically created) Measure implementations.
Other regression measures:
mlr_measures_regr.bias,
mlr_measures_regr.ktau,
mlr_measures_regr.mae,
mlr_measures_regr.mape,
mlr_measures_regr.maxae,
mlr_measures_regr.medae,
mlr_measures_regr.medse,
mlr_measures_regr.mse,
mlr_measures_regr.msle,
mlr_measures_regr.pbias,
mlr_measures_regr.rmse,
mlr_measures_regr.rmsle,
mlr_measures_regr.rrse,
mlr_measures_regr.rse,
mlr_measures_regr.rsq,
mlr_measures_regr.sae,
mlr_measures_regr.smape,
mlr_measures_regr.srho,
mlr_measures_regr.sse