caret (version 3.21)

trainControl: Control parameters for train

Description

Control of printing and resampling for train

Usage

trainControl(
   method = "boot", 
   number = ifelse(method == "cv", 10, 25), 
   verboseIter = TRUE, 
   returnData = TRUE, 
   p = 0.5, 
   selectionFunction = "best",
   index = NULL)

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,

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

selectionFunction

the function used to select the optimal tuning parameter. This can be a name of the function or the funciton itself. See best for details and other options.

index

a list with elements for each resampling iteration. Each list element is the sample rows used for training at that iteration.

Value

• An echo of the parameters specified