trainNWSControl {caretNWS}R Documentation

Control parameters for train

Description

Control of printing and resampling for trainNWS

Usage

trainNWSControl(
   method = "boot", 
   number = ifelse(method == "cv", 10, 25), 
   verboseIter = TRUE, 
   returnData = TRUE, 
   p = 0.5, 
   index = NULL,
   start = startNWS)

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.
start a function that starts a slighPro object. See the link{startNWS} function in this package as an example

Value

An echo of the parameters specified

Author(s)

max Kuhn


[Package caretNWS version 0.12 Index]