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
See Also
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)
Community examples
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