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Print a Random Planted Forest

Source: R/print.R
print.rpf.Rd

Shows a forest (class rpf, from rpf() with prune = FALSE): the kind of model and its formula, the number of tree families and of splits (with how the splits were chosen), the predictors and the interaction order, whether the forest is purified, the settings of the split search and the number of threads. A pruned model, the default of rpf(), is printed by print.rpf_pruned().

Usage

# S3 method for class 'rpf'
print(x, ...)

Arguments

x

[rpf]: A fitted rpf model.

...

Further arguments passed to or from other methods.

Value

Invisibly: x.

See also

rpf(), print.rpf_pruned().

Examples

rpf(mpg ~ cyl + wt + drat, data = mtcars, max_interaction = 2, n_families = 10, prune = FALSE)
#> ── Regression Random Planted Forest ────────────────────────────────────────────
#> Formula: `mpg ~ cyl + wt + drat`
#> 10 tree families with 6 splits each on 3 predictors, interactions to degree 2.
#> ℹ `n_splits` chosen out of bag (lowest corrected OOB RMSE 2.723); growing stopped at
#> 12 splits.
#> ℹ Forest is not purified.
#> 
#> ── Tree growing 
#>      split_structure: leaf
#>   n_try_split_points: 3
#>     share_candidates: 0.1
#>       max_candidates: 50
#>     split_decay_rate: 0.1
#>        delete_leaves: TRUE
#> 
#> ℹ Fit using 1 thread, also the default for `predict()` and `purify()`.