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fp

False Positives

Description

Classification measure counting the false positives (type 1 error), i.e. the number of predictions indicating a positive class label while in fact it is negative.

Usage

fp(truth, response, positive, ...)

Arguments

truth

(factor())
True (observed) labels. Must have the exactly same two levels and the same length as response.
response

(factor())
Predicted response labels. Must have the exactly same two levels and the same length as truth.
positive

(character(1))
Name of the positive class.
...

(any)
Additional arguments. Currently ignored.

Value

Performance value as numeric(1).

Meta Information

  • Type: "binary"

  • Range: [0, Inf)

  • Minimize: TRUE

  • Required prediction: response

References

See Also

Other Binary Classification Measures: auc(), bbrier(), dor(), fbeta(), fdr(), fnr(), fn(), fomr(), fpr(), mcc(), npv(), ppv(), prauc(), tnr(), tn(), tpr(), tp()

Examples

set.seed(1)
lvls = c("a", "b")
truth = factor(sample(lvls, 10, replace = TRUE), levels = lvls)
response = factor(sample(lvls, 10, replace = TRUE), levels = lvls)
fp(truth, response, positive = "a")
mlr3measures

Performance Measures for 'mlr3'

v0.3.1
LGPL-3
Authors
Michel Lang [cre, aut] (<https://orcid.org/0000-0001-9754-0393>), Martin Binder [ctb]
Initial release

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