set_reward_kernel_bandwidth

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

set_reward_kernel_bandwidth function

<dl><dt>lnr</dt>
<dd>The learner to modify</dd>
<dt>...</dt>
<dd>Refer to the Julia documentation for available parameters.</dd></dl>

Arguments

Requires IAI version 2.2 or higher.

IAI Compatibility

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

Save a new reward kernel bandwidth inside a learner, and return new reward
predictions generated using this bandwidth for the original data used to
train the learner. — set_reward_kernel_bandwidth

<dl>

<dt>lnr</dt>
<dd>The learner to modify</dd>


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

</dl>

Requires IAI version 2.2 or higher.

Save a new reward kernel bandwidth inside a learner, and return new reward
predictions generated using this bandwidth for the original data used to
train the learner.

set_reward_kernel_bandwidth: Save a new reward kernel bandwidth inside a learner, and return new reward predictions generated using this bandwidth for the original data used to train the learner.

Description

Usage

Arguments

IAI Compatibility

Examples