SuperLearner.control

Control parameters for the <code>SuperLearner</code>

utilities

Implements the super learner prediction method and contains a
library of prediction algorithms to be used in the super learner.

Eric Polley

SuperLearner

Super Learner Prediction

Erin LeDell

Chris Kennedy

Sam Lendle

Mark van der Laan

SuperLearner.control function

<dl> <dt>saveFitLibrary</dt>
<dd>Logical. Should the fit for each algorithm be saved in the output from <code>SuperLearner</code>.</dd> <dt>saveCVFitLibrary</dt>
<dd>Logical. Should cross-validated fits for each algorithm be saved in the output from <code>SuperLearner</code>.</dd> <dt>trimLogit</dt>
<dd>number between 0.0 and 0.5. What level to truncate the logit transformation to maintain a bounded loss function when using the NNloglik method.</dd></dl>

Arguments

Control parameters for the SuperLearner — SuperLearner.control

<dl>

 <dt>saveFitLibrary</dt>
<dd>Logical. Should the fit for each algorithm be saved in the output from <code>SuperLearner</code>.</dd>

 <dt>saveCVFitLibrary</dt>
<dd>Logical. Should cross-validated fits for each algorithm be saved in the output from <code>SuperLearner</code>.</dd>

 <dt>trimLogit</dt>
<dd>number between 0.0 and 0.5. What level to truncate the logit transformation to maintain a bounded loss function when using the NNloglik method.</dd>

</dl>

SuperLearner.control: Control parameters for the SuperLearner

Description

Usage

Value

Arguments