mlr3measures (version 0.3.1)

ktau: Kendall's tau

Description

Regression measure defined as Kendall's rank correlation coefficient between truth and response. Calls stats::cor() with method set to "kendall".

Usage

ktau(truth, response, ...)

Arguments

truth

(numeric()) True (observed) values. Must have the same length as response.

response

(numeric()) Predicted response values. Must have the same length as truth.

...

(any) Additional arguments. Currently ignored.

Value

Performance value as numeric(1).

Meta Information

  • Type: "regr"

  • Range: \([-1, 1]\)

  • Minimize: FALSE

  • Required prediction: response

References

Rosset S, Perlich C, Zadrozny B (2006). “Ranking-based evaluation of regression models.” Knowledge and Information Systems, 12(3), 331--353. 10.1007/s10115-006-0037-3.

See Also

Other Regression Measures: bias(), mae(), mape(), maxae(), maxse(), medae(), medse(), mse(), msle(), pbias(), rae(), rmse(), rmsle(), rrse(), rse(), rsq(), sae(), smape(), srho(), sse()

Examples

Run this code
# NOT RUN {
set.seed(1)
truth = 1:10
response = truth + rnorm(10)
ktau(truth, response)
# }

Run the code above in your browser using DataCamp Workspace