fit.imputation_learner

Additional keyword arguments are available for fitting imputation learners -
please refer to the Julia documentation.

An interface to the algorithms of 'Interpretable AI'
<https://www.interpretable.ai> from the R programming language.
'Interpretable AI' provides various modules, including 'Optimal Trees' for
classification, regression, prescription and survival analysis, 'Optimal
Imputation' for missing data imputation and outlier detection, and 'Optimal
Feature Selection' for exact sparse regression. The 'iai' package is an
open-source project. The 'Interpretable AI' software modules are proprietary
products, but free academic and evaluation licenses are available.

Jack Dunn

Interface to 'Interpretable AI' Modules

Ying Zhuo

Interpretable AI LLC 

fit.imputation_learner function

<dl><dt>obj</dt>
<dd>The learner or grid to fit.</dd>
<dt>X</dt>
<dd>The features of the data.</dd>
<dt>...</dt>
<dd>Refer to the Julia documentation for available parameters.</dd></dl>

Arguments

Fits an imputation learner to the training data. — fit.imputation_learner

<dl>

<dt>obj</dt>
<dd>The learner or grid to fit.</dd>


<dt>X</dt>
<dd>The features of the data.</dd>


<dt>...</dt>
<dd>Refer to the Julia documentation for available parameters.</dd>

</dl>

fit.imputation_learner: Fits an imputation learner to the training data.

Description

Usage

Arguments

Details

Examples