plot.ExclusiveLassoFit: Visualizing Exclusive Lasso Regularization Paths

In DataSlingers/ExclusiveLasso: Generalized Linear Models with the Exclusive Lasso Penalty

Description

Visualizing Exclusive Lasso Regularization Paths

Usage

## S3 method for class 'ExclusiveLassoFit'
plot(
  x,
  xvar = c("norm", "lambda", "l1"),
  label = FALSE,
  legend = "topright",
  ...
)

Arguments

x	An ExclusiveLassoFit object produced by exclusive_lasso
xvar	Value to use on the x-axis (ordinate). norm: The value of the composite l2/l1 norm "exclusive lasso" norm lambda: The log of the regularization parameter lambda. l1: The l1-norm of the solution
label	Should variables be labeled? Set label=NULL to label only those variables which are non-zero at the sparsest end of the regularization path.
legend	Should a legend of top variables (heuristically selcted) be displayed? Set legend=NULL to disable, else give the location of the legend.
...	Additional arguments passed to plotting functions n <- 200 p <- 500 groups <- rep(1:10, times=50) beta <- numeric(p); beta[1:10] <- 3 X <- matrix(rnorm(n * p), ncol=p) y <- X exfit <- exclusive_lasso(X, y, groups) plot(exfit) plot(exfit, legend=NULL, xvar="lambda")

DataSlingers/ExclusiveLasso documentation built on April 17, 2020, 4:11 a.m.