update.safs

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Update or Re-fit a SA or GA Model

update allows a user to over-ride the search iteration selection process.

Based on the results of plotting a gafs or safs object, these functions can be used to supersede the number of iterations determined analytically from the resamples.

Any values of ... originally passed to gafs or safs are automatically passed on to the updated model (i.e. they do not need to be supplied again to update.

Keywords
models
Usage
# S3 method for safs
update(object, iter, x, y, ...)
Arguments
object

An object produced by gafs or safs

iter

a single numeric integer

x, y

the original training data used in the call to gafs or safs

not currently used

Value

an object of class gafs or safs

See Also

gafs, safs

Aliases
  • update.safs
  • update.gafs
Examples
# NOT RUN {
# }
# NOT RUN {
set.seed(1)
train_data <- twoClassSim(100, noiseVars = 10)
test_data  <- twoClassSim(10,  noiseVars = 10)

## A short example
ctrl <- safsControl(functions = rfSA,
                    method = "cv",
                    number = 3)

rf_search <- safs(x = train_data[, -ncol(train_data)],
                  y = train_data$Class,
                  iters = 3,
                  safsControl = ctrl)

rf_search2 <- update(rf_search,
	                 iter = 1,
	                 x = train_data[, -ncol(train_data)],
                     y = train_data$Class)
rf_search2
# }
Documentation reproduced from package caret, version 6.0-80, License: GPL (>= 2)

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