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mlr3measures (version 0.3.0)

pbias: Percent Bias

Description

Regression measure defined as $$ \frac{1}{n} \sum_{i=1}^n \frac{\left( t_i - r_i \right)}{\left| t_i \right|}. $$ Good predictions score close to 0.

Usage

pbias(truth, response, na_value = NaN, ...)

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.

na_value

:: numeric(1) Value that should be returned if the measure is not defined for the input (as described in the note). Default is NaN.

...

:: any Additional arguments. Currently ignored.

Value

Performance value as numeric(1).

Meta Information

  • Type: "regr"

  • Range: \((-\infty, \infty)\)

  • Minimize: NA

  • Required prediction: response

See Also

Other Regression Measures: bias(), ktau(), mae(), mape(), maxae(), maxse(), medae(), medse(), mse(), msle(), 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)
pbias(truth, response)
# }

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