permute_process_variables

Take a dataframe and build a larger dataframe by permuting the
values in the columns corresponding to <code>variable_levels</code>.

internal

Aims to make machine learning in healthcare as easy as possible.
You can develop customized, reliable, high-performance machine learning models with minimal code.
Models are created with automatic preprocessing, hyperparameter tuning, and
algorithm selection (between
'xgboost' Chen, T. & Guestrin, C. (2016) <arXiv:1603.02754>,
'ranger' Wright, M. N., & Ziegler, A. (2017) <doi:10.18637/jss.v077.i01>,
and 'glm' Friedman J, Hastie T, Tibshirani R. (2010) <doi:10.18637/jss.v033.i01>)
so that they can be easily
put into production. Additionally, there are tools to help understand how a model makes its
predictions, select prediction threshholds for operational use, and evaluate model performance over time.
Code uses 'tidyverse' syntax and most methods have an associated visualization.

Mike Mastanduno

healthcareai

Tools for Healthcare Machine Learning

Levi Thatcher

Michael Levy

Taylor Larsen

Taylor Miller

Rex Sumsion

permute_process_variables function

<dl><dt>dataframe</dt>
<dd>A dataframe.</dd>
<dt>variable_levels</dt>
<dd>A list indexed by the modifiable
process variables and containing the factor levels of each such variable.</dd></dl>

Arguments

Take a dataframe and build a larger dataframe by permuting the
values in certain columns. — permute_process_variables

<dl>

<dt>dataframe</dt>
<dd>A dataframe.</dd>


<dt>variable_levels</dt>
<dd>A list indexed by the modifiable
process variables and containing the factor levels of each such variable.</dd>

</dl>

permute_process_variables: Take a dataframe and build a larger dataframe by permuting the values in certain columns.

Description

Usage

Value

Arguments