Plot model comparison

Usage

tl_plot_model_comparison(..., new_data = NULL, metrics = NULL, names = NULL)

Arguments

...: tidylearn model objects to compare
new_data: Optional data frame for evaluation. If NULL, the models are scored on their training data, which they must share: models fitted on different data are an error asking for new_data. A model fitted on engineered features, as tl_auto_ml() builds some of its candidates, is scored on the training data of the others.
metrics: Character vector of metrics to compute
names: Optional character vector of model names

Value

A ggplot object.

Examples

# \donttest{
m1 <- tl_model(mtcars, mpg ~ wt + hp, method = "linear")
m2 <- tl_model(mtcars, mpg ~ wt + hp, method = "lasso")
tl_plot_model_comparison(m1, m2, names = c("Linear", "Lasso"))
#> Evaluating on training data. For model validation, provide separate test data.

# }