relinkCPP_prt

When a `foresty` object is saved and then reloaded the Cpp
 pointers for the data set and the Cpp forest have to be reconstructed

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

relinkCPP_prt function

<dl><dt>object</dt>
<dd>an object of class `forestry` or class `multilayerForestry`</dd></dl>

Arguments

relink CPP ptr — relinkCPP_prt

<dl>

<dt>object</dt>
<dd>an object of class `forestry` or class `multilayerForestry`</dd>

</dl>

relinkCPP_prt: relink CPP ptr

Description

Usage

Arguments