predict-multilayer-forestry

predict.multilayerForestry

Return the prediction from the forest.

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

predict-multilayer-forestry function

<dl><dt>object</dt>
<dd>A `multilayerForestry` object.</dd>
<dt>feature.new</dt>
<dd>A data frame of testing predictors.</dd>
<dt>aggregation</dt>
<dd>How shall the leaf be aggregated. The default is to return
the mean of the leave `average`. Other options are `weightMatrix`.</dd>
<dt>seed</dt>
<dd>random seed</dd>
<dt>...</dt>
<dd>additional arguments.</dd></dl>

Arguments

predict-multilayer-forestry — predict-multilayer-forestry

<dl>

<dt>object</dt>
<dd>A `multilayerForestry` object.</dd>


<dt>feature.new</dt>
<dd>A data frame of testing predictors.</dd>


<dt>aggregation</dt>
<dd>How shall the leaf be aggregated. The default is to return
the mean of the leave `average`. Other options are `weightMatrix`.</dd>


<dt>seed</dt>
<dd>random seed</dd>


<dt>...</dt>
<dd>additional arguments.</dd>

</dl>

predict-multilayer-forestry: predict-multilayer-forestry

Description

Usage

Value

Arguments