Evaluate the performance of a ModelLm
using the Bayesian information criterion.
See also
EvaluatorAIC()
to get Akaike information criterion (AIC), 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"))
EvaluatorBIC(mod_fit)
#> [1] 424.8929