robustNormalize

A function that normalizes continous by the interquartile range and
optionally forces the resulting values to be between -3 and 3 with
f(x) = x / sqrt(1 + (x/3)^2)
'@details uses (value - median) / iqr to normalize the data and then can
applies the function f(x) = x / sqrt(1 + (x/3)^2) to the normalized values.
This forces the values to be between -3 and 3 while preserving the relative
ordering of the values.
based on https://arxiv.org/abs/2407.04491 for more details

internal

A user friendly way to create patient level prediction models using
the Observational Medical Outcomes Partnership Common Data Model. Given a cohort
of interest and an outcome of interest, the package can use data in the Common
Data Model to build a large set of features. These features can then be used to
fit a predictive model with a number of machine learning algorithms. This is
further described in Reps (2017) <doi:10.1093/jamia/ocy032>.

Egill Fridgeirsson

PatientLevelPrediction

Develop Clinical Prediction Models Using the Common Data Model

Jenna Reps

Martijn Schuemie

Marc Suchard

Patrick Ryan

Peter Rijnbeek

Observational Health Data Science and Informatics 

robustNormalize function

<dl><dt>trainData</dt>
<dd>The training data to be normalized</dd>
<dt>featureEngineeringSettings</dt>
<dd>The settings for the normalization</dd>
<dt>done</dt>
<dd>Whether the data has already been normalized (bool)</dd></dl>

Arguments

A function that normalizes continous by the interquartile range and
optionally forces the resulting values to be between -3 and 3 with
f(x) = x / sqrt(1 + (x/3)^2)
'@details uses (value - median) / iqr to normalize the data and then can
applies the function f(x) = x / sqrt(1 + (x/3)^2) to the normalized values.
This forces the values to be between -3 and 3 while preserving the relative
ordering of the values.
based on https://arxiv.org/abs/2407.04491 for more details — robustNormalize

<dl>

<dt>trainData</dt>
<dd>The training data to be normalized</dd>


<dt>featureEngineeringSettings</dt>
<dd>The settings for the normalization</dd>


<dt>done</dt>
<dd>Whether the data has already been normalized (bool)</dd>

</dl>

A function that normalizes continous by the interquartile range and
optionally forces the resulting values to be between -3 and 3 with
f(x) = x / sqrt(1 + (x/3)^2)
'@details uses (value - median) / iqr to normalize the data and then can
applies the function f(x) = x / sqrt(1 + (x/3)^2) to the normalized values.
This forces the values to be between -3 and 3 while preserving the relative
ordering of the values.
based on https://arxiv.org/abs/2407.04491 for more details

Description

Usage

Value

Arguments