variable_importance

Generic function for calculating variable importance

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 

variable_importance function

<dl><dt>obj</dt>
<dd>The object controlling which method is used</dd>
<dt>...</dt>
<dd>Arguments depending on the specific method used</dd></dl>

Arguments

Generic function for calculating variable importance — variable_importance

<dl>

<dt>obj</dt>
<dd>The object controlling which method is used</dd>


<dt>...</dt>
<dd>Arguments depending on the specific method used</dd>

</dl>

variable_importance: Generic function for calculating variable importance

Description

Usage

Arguments