mlr3measures: confusion_matrix – R documentation

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

confusion_matrix

Calculate Binary Confusion Matrix

Description

Calculates the confusion matrix for a binary classification problem once and then calculates all confusion measures of this package.

Usage

confusion_matrix(truth, response, positive, na_value = NaN, relative = FALSE)

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.
`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`.
`relative`	(`logical(1)`) If `TRUE`, the returned confusion matrix contains relative frequencies instead of absolute frequencies.

Value

List with two elements:

matrix stores the calculated confusion matrix.
measures stores the metrics as named numeric vector.

Examples

set.seed(123)
lvls = c("a", "b")
truth = factor(sample(lvls, 20, replace = TRUE), levels = lvls)
response = factor(sample(lvls, 20, replace = TRUE), levels = lvls)

confusion_matrix(truth, response, positive = "a")
confusion_matrix(truth, response, positive = "a", relative = TRUE)
confusion_matrix(truth, response, positive = "b")

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