mlr3measures (version 0.3.0)

ce: Classification Error

Description

Classification measure defined as $$ \frac{1}{n} \sum_{i=1}^n \left( t_i \neq r_i \right). $$

Usage

ce(truth, response, ...)

Arguments

truth

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

response

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

...

:: any Additional arguments. Currently ignored.

Value

Performance value as numeric(1).

Meta Information

• Type: "classif"

• Range: \([0, 1]\)

• Minimize: TRUE

• Required prediction: response

See Also

Other Classification Measures: acc(), bacc(), logloss(), mauc_aunu(), mbrier()

Examples

# NOT RUN {
set.seed(1)
lvls = c("a", "b", "c")
truth = factor(sample(lvls, 10, replace = TRUE), levels = lvls)
response = factor(sample(lvls, 10, replace = TRUE), levels = lvls)
ce(truth, response)
# }