PatientLevelPrediction (version 3.0.0)

setRandomForest: Create setting for random forest model with python (very fast)

Description

Create setting for random forest model with python (very fast)

Usage

setRandomForest(mtries = -1, ntrees = 500, maxDepth = c(4, 10, 17),
  varImp = T, seed = NULL)

Arguments

mtries

The number of features to include in each tree (-1 defaults to square root of total features)

ntrees

The number of trees to build

maxDepth

Maximum number of interactions - a large value will lead to slow model training

varImp

Perform an initial variable selection prior to fitting the model to select the useful variables

seed

An option to add a seed when training the final model

Examples

# NOT RUN {
model.rf <- setRandomForest(mtries=c(-1,5,20),  ntrees=c(10,100), 
                           maxDepth=c(5,20))
# }