predict_shap

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

predict_shap function

<dl><dt>lnr</dt>
<dd>The XGBoost learner or grid to use for prediction.</dd>
<dt>X</dt>
<dd>The features of the data.</dd></dl>

Arguments

Requires IAI version 2.2 or higher.

IAI Compatibility

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

Calculate SHAP values for all points in the features using the learner — predict_shap

<dl>

<dt>lnr</dt>
<dd>The XGBoost learner or grid to use for prediction.</dd>


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

</dl>

Requires IAI version 2.2 or higher.

predict_shap: Calculate SHAP values for all points in the features using the learner

Description

Usage

Arguments

IAI Compatibility

Examples