Plot Method for the gafs and safs Classes

Plot the performance values versus search iteration

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

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

# S3 method for 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.

Value

Either a data frame, ggplot object or lattice object

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.

See also

gafs, safs, ggplot, xyplot

Examples

if (FALSE) {
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)
    }