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

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) The number of trees to build Maximum number of interactions - a large value will lead to slow model training Perform an initial variable selection prior to fitting the model to select the useful variables 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))
# }