mlr3measures (version 1.0.0)

maxse: Max Squared Error

Description

Measure to compare true observed response with predicted response in regression tasks.

Usage

maxse(truth, response, ...)

Value

Performance value as numeric(1).

Arguments

truth

(numeric())
True (observed) values. Must have the same length as response.

response

(numeric())
Predicted response values. Must have the same length as truth.

...

(any)
Additional arguments. Currently ignored.

Meta Information

• Type: "regr"

• Range: \([0, \infty)\)

• Minimize: TRUE

• Required prediction: response

Details

The Max Squared Error is defined as $$ \max \left( t_i - r_i \right)^2. $$

See Also

Other Regression Measures: ae(), ape(), bias(), ktau(), linex(), mae(), mape(), maxae(), medae(), medse(), mse(), msle(), pbias(), pinball(), rae(), rmse(), rmsle(), rrse(), rse(), rsq(), sae(), se(), sle(), smape(), srho(), sse()

Examples

set.seed(1)
truth = 1:10
response = truth + rnorm(10)
maxse(truth, response)