1d:T71c,# 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. ```r ## S3 method for class 'rfe' densityplot(x, data = NULL, metric = x$metric, ...) ``` ## Arguments - `x`: An object produced by `rfe` - `data`: This argument is not used - `metric`: A character string specifying the single performance metric that will be plotted - ``...``: arguments to pass to either `histogram`, `densityplot`, `xyplot` or `stripplot` ## Returns A lattice plot object ## Details By default, only the resampling results for the optimal model are saved in the `rfe` object. The function `rfeControl` can be used to save all the results using the `returnResamp` argument. If leave-one-out or out-of-bag resampling was specified, plots cannot be produced (see the `method` argument of `rfeControl`) ## Examples ```r ## Not run: library(mlbench) n <- 100 p <- 40 sigma <- 1 set.seed(1) sim <- mlbench.friedman1(n, sd = sigma) x <- cbind(sim$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, stringsAsFactors = TRUE) 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) ``` ## See Also `rfe`, `rfeControl`, `histogram`, `densityplot`, `xyplot`, `stripplot` ## Author(s) Max Kuhn1e:T49a,M7.49933 0.25C3.49635 0.25 0.25 3.49593 0.25 7.50024C0.25 10.703 2.32715 13.4206 5.2081 14.3797C5.57084 14.446 5.70302 14.2222 5.70302 14.0299C5.70302 13.8576 5.69679 13.4019 5.69323 12.797C3.67661 13.235 3.25112

densityplot.rfe function