lattice.rfe

From caret v4.62 by Max Kuhn

Lattice functions for plotting resampling results of recursive feature selection

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

Keywords: hplot

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

x: 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

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)

Value

A lattice plot object

Examples

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)

Documentation reproduced from package caret, version 4.62, License: GPL-2

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