update.train

0th

Percentile

Update and Re-fit a Model

update allows a user to over-ride the tuning parameter selection process by specifying a set of tuning parameters.

Keywords
models
Usage
## S3 method for class 'train':
update(object, param = NULL, ...)
Arguments
object
an object of class train
param
a data frame or named list of all tuning parameters
...
not currently used
Details

To update the model, the training data must be stored in the model object (see the option returnData in trainControl. Also, all tuning parameters must be specified (with the preceding dot in the name).

All other options are held constant, including the original pre-processing (if any), options passed in using code{...} and so on.

When printing, the verbiage "The tuning parameter was set manually." is used to describe how the tuning parameters were created.

Value

See Also

train, trainControl

Aliases
  • update.train
Examples
data(iris)
TrainData <- iris[,1:4]
TrainClasses <- iris[,5]

knnFit1 <- train(TrainData, TrainClasses,
                 method = "knn",
                 preProcess = c("center", "scale"),
                 tuneLength = 10,
                 trControl = trainControl(method = "cv"))

update(knnFit1, list(.k = 3))
Documentation reproduced from package caret, version 5.15-044, License: GPL-2

Community examples

Looks like there are no examples yet.