Classification measure counting the false negatives (type 2 error), i.e. the number of predictions indicating a negative class label while in fact it is positive. This is sometimes also called a "false alarm".


The score function calls mlr3measures::fn() from package mlr3measures.

If the measure is undefined for the input, NaN is returned. This can be customized by setting the field na_value.


This Measure can be instantiated via the dictionary mlr_measures or with the associated sugar function msr():


Meta Information

  • Type: "binary"

  • Range: \([0, \infty)\)

  • Minimize: TRUE

  • Required prediction: response

See also