PatientLevelPrediction (version 4.3.10)

setLassoLogisticRegression: Create setting for lasso logistic regression

Description

Create setting for lasso logistic regression

Usage

setLassoLogisticRegression(
  variance = 0.01,
  seed = NULL,
  includeCovariateIds = c(),
  noShrinkage = c(0),
  threads = -1,
  useCrossValidation = TRUE,
  upperLimit = 20,
  lowerLimit = 0.01
)

Arguments

variance

a single value used as the starting value for the automatic lambda search

seed

An option to add a seed when training the model

includeCovariateIds

a set of covariate IDS to limit the analysis to

noShrinkage

a set of covariates whcih are to be forced to be included in the final model. default is the intercept

threads

An option to set number of threads when training model

useCrossValidation

Set this to FALSE if you want to train a LR with a preset varience

upperLimit

Upper prior variance limit for grid-search

lowerLimit

Lower prior variance limit for grid-search

Examples

# NOT RUN {
model.lr <- setLassoLogisticRegression()
# }