fit.optimal_feature_selection_learner

When the <code>coordinated_sparsity</code> parameter of the learner is <code>TRUE</code>,
additional keyword arguments are required - 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.optimal_feature_selection_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>Other parameters, including zero or more target vectors as
required by the problem type. Refer to the Julia documentation for
available parameters.</dd></dl>

Arguments

Requires IAI version 1.1 or higher.

IAI Compatibility

Fits an Optimal Feature Selection learner to the training data — fit.optimal_feature_selection_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>Other parameters, including zero or more target vectors as
required by the problem type. Refer to the Julia documentation for
available parameters.</dd>

</dl>

Requires IAI version 1.1 or higher.

fit.optimal_feature_selection_learner: Fits an Optimal Feature Selection learner to the training data

Description

Usage

Arguments

IAI Compatibility

Details

Examples