Measure to compare true observed response with predicted response in regression tasks.
This Measure can be instantiated via the dictionary mlr_measures or with the associated sugar function msr():
mlr_measures$get("regr.ktau")
msr("regr.ktau")
Empty ParamSet
Type: "regr"
Range: \([-1, 1]\)
Minimize: FALSE
Required prediction: response
Kendall's tau is defined as Kendall's rank correlation coefficient between truth and response.
It is defined as $$
\tau = \frac{(\mathrm{number of concordant pairs)} - (\mathrm{number of discordant pairs)}}{\mathrm{(number of pairs)}}
$$
Calls stats::cor() with method set to "kendall".
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.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.pinball,
mlr_measures_regr.rae,
mlr_measures_regr.rmse,
mlr_measures_regr.rmsle,
mlr_measures_regr.rrse,
mlr_measures_regr.rse,
mlr_measures_regr.sae,
mlr_measures_regr.smape,
mlr_measures_regr.srho,
mlr_measures_regr.sse