trainLSFControl {caretLSF}R Documentation

Control parameters for train

Description

Control of printing and resampling for trainLSF

Usage

trainLSFControl(
   method = "boot", 
   number = ifelse(method == "cv", 10, 25), 
   verboseIter = TRUE, 
   returnData = TRUE, 
   p = 0.5, 
   index = NULL,
   numWorkers = 5,
   buffer = 20,
   pause = 10,   
   lsf = lsf.ctrl())

Arguments

method The resampling method: boot, cv, LOOCV, LGOCV (for repeated training/test splits), or oob (only for random forest, bagged trees, bagged earth, bagged flexible discriminant analysis, or conditional tree forest models)
number Either the number of folds or number of resampling iterations
verboseIter A logical for printing a training log.
returnData A logical for saving the data
p For leave-group out cross-validation: the training percentage
index a list with elements for each resampling iteration. Each list element is the sample rows used for training at that iteration.
numWorkers the number of nodes that the job should be split across
buffer a multiplier for the job kill threshold: how many times slower than the slowest job does a task have to be before it is stopped
pause number of seconds between checking the current jobs
lsf a list of optional control parameters for submitting jobs. See lsf.ctrl for more details

Value

An echo of the parameters specified

Author(s)

max Kuhn


[Package caretLSF version 1.14 Index]