lattice.rfe: Lattice functions for plotting resampling results of recursive feature selection

Description

A set of lattice functions are provided to plot the resampled performance estimates (e.g. classification accuracy, RMSE) over different subset sizes.

Usage

## S3 method for class 'rfe':
histogram(x, data = NULL, metric = x$metric, ...)
## S3 method for class 'rfe':
densityplot(x, data = NULL, metric = x$metric, ...)
## S3 method for class 'rfe':
xyplot(x, data = NULL, metric = x$metric, ...)
## S3 method for class 'rfe':
stripplot(x, data = NULL, metric = x$metric, ...)

Arguments

An object produced by rfe

data

This argument is not used

metric

A character string specifying the single performance metric that will be plotted

...

arguments to pass to either histogram, densityplot, xyplot

Value

A lattice plot object

Details

By default, only the resampling results for the optimal model are saved in the rfe object. The function rfeControl can be used to save all the results using the returnResamp argument.

If leave-one-out or out-of-bag resampling was specified, plots cannot be produced (see the method argument of rfeControl)

Examples

Run this code

library(mlbench)
n <- 100
p <- 40
sigma <- 1
set.seed(1)
sim <- mlbench.friedman1(n, sd = sigma)
x <- cbind(sim$x,  matrix(rnorm(n * p), nrow = n))
y <- sim$y
colnames(x) <- paste("var", 1:ncol(x), sep = "")

normalization <- preProcess(x)
x <- predict(normalization, x)
x <- as.data.frame(x)
subsets <- c(10, 15, 20, 25)

ctrl <- rfeControl(
                   functions = lmFuncs,
                   method = "cv",
                   verbose = FALSE,
                   returnResamp = "all")

lmProfile <- rfe(x, y,
                 sizes = subsets,
                 rfeControl = ctrl)
xyplot(lmProfile)
stripplot(lmProfile)

histogram(lmProfile)
densityplot(lmProfile)

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