rf_classifier

Given a model object (e.g. <code>projector</code> construct a random forest classifier that can generate predictions for new data points.

Provides a set of basic and extensible data structures and functions for multivariate analysis, including dimensionality reduction techniques, projection methods, and preprocessing functions. The aim of this package is to offer a flexible and user-friendly framework for multivariate analysis that can be easily extended for custom requirements and specific data analysis tasks.

Bradley Buchsbaum

multivarious

Extensible Data Structures for Multivariate Analysis

rf_classifier function

<dl><dt>x</dt>
<dd>the model object</dd>
<dt>colind</dt>
<dd>the (optional) column indices used for prediction</dd>
<dt>...</dt>
<dd>extra arguments to <code>randomForest</code> function</dd></dl>

Arguments

construct a random forest wrapper classifier — rf_classifier

<dl>

<dt>x</dt>
<dd>the model object</dd>


<dt>colind</dt>
<dd>the (optional) column indices used for prediction</dd>


<dt>...</dt>
<dd>extra arguments to <code>randomForest</code> function</dd>

</dl>

rf_classifier: construct a random forest wrapper classifier

Description

Usage

Value

Arguments