tidyCovariateData {FeatureExtraction} | R Documentation |
Tidy covariate data
Description
Tidy covariate data
Usage
tidyCovariateData(
covariateData,
minFraction = 0.001,
normalize = TRUE,
removeRedundancy = TRUE
)
Arguments
covariateData |
An object as generated using the |
minFraction |
Minimum fraction of the population that should have a non-zero value for a covariate for that covariate to be kept. Set to 0 to don't filter on frequency. |
normalize |
Normalize the covariates? (dividing by the max). |
removeRedundancy |
Should redundant covariates be removed? |
Details
Normalize covariate values by dividing by the max and/or remove redundant covariates and/or remove infrequent covariates. For temporal covariates, redundancy is evaluated per time ID.
Value
An object of class CovariateData
.
Examples
covariateData <- FeatureExtraction::createEmptyCovariateData(
cohortIds = 1,
aggregated = FALSE,
temporal = FALSE
)
covData <- tidyCovariateData(
covariateData = covariateData,
minFraction = 0.001,
normalize = TRUE,
removeRedundancy = TRUE
)
[Package FeatureExtraction version 3.6.0 Index]