createRareFeatureRemover: Create the settings for removing rare features

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

Create the settings for removing rare features

Description

Create the settings for removing rare features

Usage

createRareFeatureRemover(threshold = 0.001)

Arguments

threshold

The minimum fraction of the training data that must have a feature for it to be included

Value

An object of class featureEngineeringSettings

Examples

 
# create a rare feature remover that removes features that are present in less
# than 1% of the population
rareFeatureRemover <- createRareFeatureRemover(threshold = 0.01)
plpData <- getEunomiaPlpData()
analysisId <- "rareFeatureRemover"
saveLocation <- file.path(tempdir(), analysisId)
results <- runPlp(
  plpData = plpData,
  featureEngineeringSettings = rareFeatureRemover,
  outcomeId = 3,
 executeSettings = createExecuteSettings(
   runModelDevelopment = TRUE,
   runSplitData = TRUE,
   runFeatureEngineering = TRUE),
 saveDirectory = saveLocation,
 analysisId = analysisId)
# clean up 
unlink(saveLocation, recursive = TRUE)
 

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