mlr3measures (version 0.3.1)

ce: Classification Error

Description

Classification measure defined as $$\frac{1}{n}\sum _{i=1}^n(t_i\ne r_i).$$

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)
# }