Learning curve of a fitted model

The loss recorded at every step of training, as data: one row per step, with the training and validation loss where the algorithm records them.

Returns NULL for an algorithm that records no learning curve, so it is safe to call on any model.

Usage

get_learning_curve(x, ...)

Arguments

x

Supervised object.

...

Additional arguments passed to methods.

Value

data.frame with columns iteration, loss_training and loss_validation, carrying attributes unit and selected; or NULL.

See also

plot_learning, which draws it

Author

EDG

Examples

if (FALSE) { # interactive()
dat <- set_outcome(iris[, 1:4], "Sepal.Length")
mod <- train(
  dat[1:100, ],
  dat_validation = dat[101:150, ],
  hyperparameters = setup_LINAD(max_leaves = 12L)
)
get_learning_curve(mod)
}