loadForestry

This wrapper function checks the forestry object, makes it
 saveable if needed, and then saves it.

Provides fast implementations of Random Forests,
Gradient Boosting, and Linear Random Forests, with an emphasis on inference
and interpretability. Additionally contains methods for variable
importance, out-of-bag prediction, regression monotonicity, and
several methods for missing data imputation.

Theo Saarinen

Rforestry

Random Forests, Linear Trees, and Gradient Boosting for
Inference and Interpretability

Sören Künzel

Simon Walter

Sam Antonyan

Edward Liu

Allen Tang

Jasjeet Sekhon

loadForestry function

<dl><dt>filename</dt>
<dd>a filename in which to store the `forestry` object</dd></dl>

Arguments

load RF — loadForestry

<dl>

<dt>filename</dt>
<dd>a filename in which to store the `forestry` object</dd>

</dl>

loadForestry: load RF

Description

Usage

Arguments