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Measure to compare true observed response with predicted response in regression tasks.

Details

The Bias is defined as $$ \frac{1}{n} \sum_{i=1}^n w_i \left( t_i - r_i \right), $$ where \(w_i\) are normalized sample weights. Good predictions score close to 0.

Note

The score function calls mlr3measures::bias() 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("regr.bias")
msr("regr.bias")

Parameters

Empty ParamSet

Meta Information

  • Type: "regr"

  • Range: \((-\infty, \infty)\)

  • Minimize: NA

  • Required prediction: response