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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)
the measure of performance to plot (e.g. RMSE, accuracy, etc)
the type of estimate: either "internal" or "external"
either "data", "ggplot" or "lattice"
For plot
methods, these are options passed
to xyplot
. For ggplot
methods,
they are not used.
kept for consistency with
ggplot
and are not used here.
Either a data frame, ggplot object or lattice object
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.
# 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 {
# }
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