mlr3measures (version 0.3.1)

tp: True Positives

Description

Binary classification measure counting the true positives, i.e. the number of predictions correctly indicating a positive class label.

Usage

tp(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: \([0, \infty)\)

  • Minimize: FALSE

  • Required prediction: response

References

https://en.wikipedia.org/wiki/Template:DiagnosticTesting_Diagram

See Also

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

Examples

Run this code
# NOT RUN {
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)
tp(truth, response, positive = "a")
# }

Run the code above in your browser using DataCamp Workspace