plot.gafs: Plot Method for the gafs and safs Classes

In caret: Classification and Regression Training

Plot Method for the gafs and safs Classes

Description

Plot the performance values versus search iteration

Usage

## S3 method for class 'gafs'
plot(
  x,
  metric = x$control$metric["external"],
  estimate = c("internal", "external"),
  output = "ggplot",
  ...
)

## S3 method for class 'gafs'
ggplot(data = NULL, mapping = NULL, ..., environment = NULL)

## S3 method for class 'safs'
ggplot(data = NULL, mapping = NULL, ..., environment = NULL)

Arguments

x	an object of class gafs or safs
metric	the measure of performance to plot (e.g. RMSE, accuracy, etc)
estimate	the type of estimate: either "internal" or "external"
output	either "data", "ggplot" or "lattice"
...	For plot methods, these are options passed to xyplot. For ggplot methods, they are not used.
data, mapping, environment	kept for consistency with ggplot and are not used here.

Details

The mean (averaged over the resamples) is plotted against the search iteration using a scatter plot.

When output = "data", the unaveraged data are returned with columns for all the performance metrics and the resample indicator.

Value

Either a data frame, ggplot object or lattice object

Author(s)

Max Kuhn

See Also

gafs, safs, ggplot, xyplot

Examples

## 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 = 50,
                  safsControl = ctrl)

plot(rf_search)
plot(rf_search,
	 output = "lattice",
	 auto.key = list(columns = 2))

plot_data <- plot(rf_search, output = "data")
summary(plot_data)
    
## End(Not run)

caret documentation built on March 31, 2023, 9:49 p.m.