plot.gafs

0th

Percentile

Plot Method for the gafs and safs Classes

Plot the performance values versus search iteration

Keywords
hplot
Usage
# 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.

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

See Also

gafs, safs, ggplot, xyplot

Aliases
  • plot.gafs
  • plot.safs
  • ggplot.gafs
  • ggplot.safs
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 = 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)
    
# }
# NOT RUN {
# }
Documentation reproduced from package caret, version 6.0-85, License: GPL (>= 2)

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