robustNormalize: A function that normalizes continous by the interquartile...

In OHDSI/PatientLevelPrediction: Develop Clinical Prediction Models Using the Common Data Model

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

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

Usage

robustNormalize(trainData, featureEngineeringSettings, done = FALSE)

Arguments

trainData	The training data to be normalized
featureEngineeringSettings	The settings for the normalization
done	Whether the data has already been normalized (bool)

Value

The trainData object with normalized data

OHDSI/PatientLevelPrediction documentation built on Feb. 14, 2025, 9:44 a.m.