# trainControl

From caret v5.15-052
by Max Kuhn

##### Control parameters for train

Control the computational nuances of the `train`

function

- Keywords
- utilities

##### Usage

```
trainControl(method = "boot",
number = ifelse(method %in% c("cv", "repeatedcv"), 10, 25),
repeats = ifelse(method %in% c("cv", "repeatedcv"), 1, number),
p = 0.75,
initialWindow = NULL,
horizon = 1,
fixedWindow = TRUE,
verboseIter = FALSE,
returnData = TRUE,
returnResamp = "final",
savePredictions = FALSE,
classProbs = FALSE,
summaryFunction = defaultSummary,
selectionFunction = "best",
custom = NULL,
preProcOptions = list(thresh = 0.95, ICAcomp = 3, k = 5),
index = NULL,
indexOut = NULL,
timingSamps = 0,
predictionBounds = rep(FALSE, 2),
allowParallel = TRUE)
```

##### Arguments

- method
- The resampling method:
`boot`

,`boot632`

,`cv`

,`repeatedcv`

,`LOOCV`

,`LGOCV`

(for repeated training/test splits), or`oob`

(only for random forest, bagged trees, bagge - number
- Either the number of folds or number of resampling iterations
- repeats
- For repeated k-fold cross-validation only: the number of complete sets of folds to compute
- verboseIter
- A logical for printing a training log.
- returnData
- A logical for saving the data
- returnResamp
- A character string indicating how much of the resampled summary metrics should be saved. Values can be ``final'', ``all'' or ``none''
- savePredictions
- a logical to save the hold-out predictions for each resample
- p
- For leave-group out cross-validation: the training percentage
- initialWindow, horizon, fixedWindow
- possible arguments to
`createTimeSlices`

- classProbs
- a logical; should class probabilities be computed for classification models (along with predicted values) in each resample?
- summaryFunction
- a function to compute performance metrics across resamples. The arguments to the function should be the same as those in
`defaultSummary`

. - custom
- an optional list of functions that can be used to fit custom models. See the details below and worked examples at
http://caret.r-forge.r-project.org/ . . This is an "experimental" version for testing. Please send emails to the maintainer for su - selectionFunction
- the function used to select the optimal tuning parameter. This can be a name of the function or the function itself. See
`best`

for details and other options. - preProcOptions
- A list of options to pass to
`preProcess`

. The type of pre-processing (e.g. center, scaling etc) is passed in via the`preProc`

option in`train`

. - index
- a list with elements for each resampling iteration. Each list element is the sample rows used for training at that iteration.
- indexOut
- a list (the same length as
`index`

) that dictates which sample are held-out for each resample. If`NULL`

, then the unique set of samples not contained in`index`

is used. - timingSamps
- the number of training set samples that will be used to measure the time for predicting samples (zero indicates that the prediction time should not be estimated.
- predictionBounds
- a logical or numeric vector of length 2 (regression only). If logical, the predictions can be constrained to be within the limit of the training set outcomes. For example, a value of
`c(TRUE, FALSE)`

would only constrain the lower end of predic - allowParallel
- if a parallel backend is loaded and available, should the function use it?

##### Details

For custom modeling functions, several functions can be specified using the `custom`

argument:

- parameters

##### Value

- An echo of the parameters specified

##### url

http://caret.r-forge.r-project.org/

*Documentation reproduced from package caret, version 5.15-052, License: GPL-2*

### Community examples

**RAVINDARMADISHETTY@GMAIL.COM**at Jul 23, 2018 caret v6.0-80

I am getting below error while submitting a text x = trainControl(method = "repeatedcv", number = numbers, repeats = repeats, classProbs = TRUE, summaryFunction = twoClassSummary) Error: Please suggesrt Error in trainControl(method = "repeatedcv", number = numbers, repeats = repeats, : could not find function "trainControl"