lattice.rfe: Lattice functions for plotting resampling results of...

In caret: Classification and Regression Training

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

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 or stripplot

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

Author(s)

Max Kuhn

See Also

rfe, rfeControl, histogram, densityplot, xyplot, stripplot

Examples

## Not run: 
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)

## End(Not run)

Example output

Loading required package: lattice
Loading required package: ggplot2

caret documentation built on May 2, 2019, 5:47 p.m.