Evaluate performance through AIC

Evaluate the performance of a ModelLm using the Akaike information criterion.

Usage

EvaluatorAIC(.model)

Arguments

.model

A ModelLm object for which the performance should be measured.

Value

The AIC value of the fitted model.

See also

EvaluatorBIC() to get the Bayesian information criterion (BIC), EvaluatorMAE() for computing the mean absolute error, EvaluatorMSE() for the mean-squared error.

Examples

cars.ds <- Dataset(data = cars, target = "dist")
mod_fit <- fit(InducerLm(), cars.ds, formula = as.formula("dist~speed"))
EvaluatorAIC(mod_fit)
#> [1] 419.1569