createPreprocessSettings {PatientLevelPrediction} | R Documentation |
Create the settings for preprocessing the trainData.
Description
Create the settings for preprocessing the trainData.
Usage
createPreprocessSettings(
minFraction = 0.001,
normalize = TRUE,
removeRedundancy = TRUE
)
Arguments
minFraction |
The minimum fraction of target population who must have a covariate for it to be included in the model training |
normalize |
Whether to normalise the covariates before training (Default: TRUE) |
removeRedundancy |
Whether to remove redundant features (Default: TRUE) Redundant features are features that within an analysisId together cover all observations. For example with ageGroups, if you have ageGroup 0-18 and 18-100 and all patients are in one of these groups, then one of these groups is redundant. |
Details
Returns an object of class preprocessingSettings
that specifies how to
preprocess the training data
Value
An object of class preprocessingSettings
Examples
# Create the settings for preprocessing, remove no features, normalise the data
createPreprocessSettings(minFraction = 0.0, normalize = TRUE, removeRedundancy = FALSE)
[Package PatientLevelPrediction version 6.4.1 Index]