fit_randomForest

Dataset, numerical matrix with observations as rows.

Sent to <code><a rd-options="randomForest" href="/link/randomForest?package=emil&version=2.2.8&to=randomForest" data-mini-rdoc="randomForest::randomForest">randomForest</a></code>.

Directly calling the randomForest package implementation. See
<code><a rd-options="randomForest" href="/link/randomForest?package=emil&version=2.2.8&to=randomForest" data-mini-rdoc="randomForest::randomForest">randomForest</a></code> for parameter specification.

A toolbox for designing and evaluating predictive models with
resampling methods. The aim of this package is to provide a simple and
efficient general framework for working with any type of prediction
problem, be it classification, regression or survival analysis, that is
easy to extend and adapt to your specific setting. Some commonly used
methods for classification, regression and survival analysis are included.

Christofer Backlin

emil

Evaluation of Modeling without Information Leakage

Mats Gustafsson

fit_randomForest function

Sent to <code><a rd-options='randomForest' href='randomForest'>randomForest</a></code>.

Directly calling the randomForest package implementation. See
<code><a rd-options='randomForest' href='randomForest'>randomForest</a></code> for parameter specification.

fit_randomForest: Fit random forest.

Description

Usage

Arguments

Value

See Also