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.

Interface to 'Interpretable AI' Modules

package-ubuntu-20.04-r-4.0.5#cran#iai-1.5.0

<p>Julia Equivalent:
<a href="https://docs.interpretable.ai/v2.1.0/OptImpute/reference/#IAI.impute_cv"><code>IAI.impute_cv</code></a>
</p>

<table summary="R argblock">
<tr valign="top">
<td><code>X</code></td>
<td>
<p>The dataframe in which to impute missing values.</p>
</td>
</tr>
<tr valign="top">
<td><code>...</code></td>
<td>
<p>Refer to the Julia documentation for available parameters.</p>
</td>
</tr>
</table>

X <- iris
X[1, 1] <- NA
iai::impute_cv(X, list(method = c("opt_knn", "opt_tree")))

package-ubuntu-20.04-r-4.0.5#cran#iai-1.5.0#docs#impute_cv

impute_cv

Description

Usage

Arguments

Examples

iai

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`X`	The dataframe in which to impute missing values.
`...`	Refer to the Julia documentation for available parameters.