mlr3measures (version 0.3.0)

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

# NOT RUN {
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")
# }