Update or Re-fit a Model
update allows a user to over-ride the tuning parameter selection
process by specifying a set of tuning parameters or to update the model
object to the latest version of this package.
## S3 method for class 'train' update(object, param = NULL, ...)
object |
an object of class |
param |
a data frame or named list of all tuning parameters |
... |
not currently used |
If the model object was created with version 5.17-7 or earlier, the
underlying package structure was different. To make old train
objects consistent with the new structure, use param = NULL to get
the same object back with updates.
To update the model parameters, the training data must be stored in the
model object (see the option returnData in
trainControl. Also, all tuning parameters must be specified in
the param slot. 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.
a new train object
Max Kuhn
## Not run:
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))
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.