variable_importance_similarity

Julia Equivalent:
<a href="https://docs.interpretable.ai/v3.2.2/IAITrees/reference/#IAI.variable_importance_similarity"><code>IAI.variable_importance_similarity</code></a>

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_similarity function

<dl><dt>lnr</dt>
<dd>The original learner</dd>
<dt>new_lnr</dt>
<dd>The new learner</dd>
<dt>...</dt>
<dd>Additional arguments (refer to Julia documentation)</dd></dl>

Arguments

Requires IAI version 2.2 or higher.

IAI Compatibility

Julia Equivalent:
<a href='https://docs.interpretable.ai/v3.2.2/IAITrees/reference/#IAI.variable_importance_similarity'><code>IAI.variable_importance_similarity</code></a>

Calculate similarity between the final tree in a tree learner with all trees
in new tree learner using variable importance scores. — variable_importance_similarity

<dl>

<dt>lnr</dt>
<dd>The original learner</dd>


<dt>new_lnr</dt>
<dd>The new learner</dd>


<dt>...</dt>
<dd>Additional arguments (refer to Julia documentation)</dd>

</dl>

Requires IAI version 2.2 or higher.

variable_importance_similarity: Calculate similarity between the final tree in a tree learner with all trees in new tree learner using variable importance scores.

Description

Usage

Arguments

IAI Compatibility

Examples