score.glmnetcv_learner

Julia Equivalent:
<a href="https://docs.interpretable.ai/v3.2.2/Heuristics/reference/#IAI.score-Tuple%7BGLMNetCVLearner%7D"><code>IAI.score</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 

score.glmnetcv_learner function

<dl><dt>obj</dt>
<dd>The learner or grid to evaluate.</dd>
<dt>X</dt>
<dd>The features of the data.</dd>
<dt>...</dt>
<dd>Other parameters, including zero or more target vectors as
required by the problem type. <code>fit_index</code> can be used to
specify the index of the fit in the path to use for prediction,
defaulting to the best fit if not supplied. Refer to the Julia
documentation for other available parameters.</dd></dl>

Arguments

Requires IAI version 2.1 or higher.

IAI Compatibility

Julia Equivalent:
<a href='https://docs.interpretable.ai/v3.2.2/Heuristics/reference/#IAI.score-Tuple%7BGLMNetCVLearner%7D'><code>IAI.score</code></a>

Calculate the score for a GLMNet learner on the given data — score.glmnetcv_learner

<dl>

<dt>obj</dt>
<dd>The learner or grid to evaluate.</dd>


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


<dt>...</dt>
<dd>Other parameters, including zero or more target vectors as
required by the problem type. <code>fit_index</code> can be used to
specify the index of the fit in the path to use for prediction,
defaulting to the best fit if not supplied. Refer to the Julia
documentation for other available parameters.</dd>

</dl>

Requires IAI version 2.1 or higher.

score.glmnetcv_learner: Calculate the score for a GLMNet learner on the given data

Description

Usage

Arguments

IAI Compatibility

Examples