feature_cor

High dimensional imputation via batch processed chained random forests
Build correlation matrix

A correlation-based batch process for fast, accurate imputation for
high dimensional missing data problems via chained random forests.
See Waggoner (2023) <doi:10.1007/s00180-023-01325-9> for more on 'hdImpute',
Stekhoven and Bühlmann (2012) <doi:10.1093/bioinformatics/btr597> for more on 'missForest',
and Mayer (2022) <https://github.com/mayer79/missRanger> for more on 'missRanger'.

Philip Waggoner

hdImpute

A Batch Process for High Dimensional Imputation

feature_cor function

<dl><dt>data</dt>
<dd>A data frame or tibble.</dd>
<dt>return_cor</dt>
<dd>Logical. Should the correlation matrix be printed? Default set to FALSE.</dd></dl>

Arguments

High dimensional imputation via batch processed chained random forests
Build correlation matrix — feature_cor

<dl>

<dt>data</dt>
<dd>A data frame or tibble.</dd>


<dt>return_cor</dt>
<dd>Logical. Should the correlation matrix be printed? Default set to FALSE.</dd>

</dl>

feature_cor: High dimensional imputation via batch processed chained random forests Build correlation matrix

Description

Usage

Value

Arguments

References

Examples