get_regression_weights.prescription_tree_learner

Julia Equivalent:
<a href="https://docs.interpretable.ai/v3.2.2/IAITrees/reference/#IAI.get_regression_weights-Tuple%7BPrescriptionTreeLearner%2C%20Int64%2C%20Any%7D"><code>IAI.get_regression_weights</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 

get_regression_weights.prescription_tree_learner function

<dl><dt>obj</dt>
<dd>The learner to query.</dd>
<dt>node_index</dt>
<dd>The node in the tree to query.</dd>
<dt>treatment</dt>
<dd>The treatment to query.</dd>
<dt>...</dt>
<dd>Refer to the Julia documentation for available parameters.</dd></dl>

Arguments

Julia Equivalent:
<a href='https://docs.interpretable.ai/v3.2.2/IAITrees/reference/#IAI.get_regression_weights-Tuple%7BPrescriptionTreeLearner%2C%20Int64%2C%20Any%7D'><code>IAI.get_regression_weights</code></a>

Return the weights for each feature in the linear regression prediction at a
node of a prescription tree — get_regression_weights.prescription_tree_learner

<dl>

<dt>obj</dt>
<dd>The learner to query.</dd>


<dt>node_index</dt>
<dd>The node in the tree to query.</dd>


<dt>treatment</dt>
<dd>The treatment to query.</dd>


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

</dl>

get_regression_weights.prescription_tree_learner: Return the weights for each feature in the linear regression prediction at a node of a prescription tree

Description

Usage

Arguments

Examples