Visualize the paths of an SDTree or SDForest

Source: R/paths.R

This function visualizes the variable importance of an SDTree or SDForest for different complexity parameters. Both the regularization path and the stability selection path can be visualized.

# S3 method for class 'paths'
plot(x, plotly = FALSE, selection = NULL, sqrt_scale = FALSE, ...)

Arguments

x

A paths object

plotly

If TRUE the plot is returned interactive using plotly. Might be slow for large data.

selection

A vector of indices of the covariates to be plotted. Can be used to plot only a subset of the covariates in case of many covariates.

sqrt_scale

If TRUE the y-axis is on a square root scale.

...

Further arguments passed to or from other methods.

Value

A ggplot object with the variable importance for different regularization. If the path object includes a cp_min value, a black dashed line is added to indicate the out-of-bag optimal variable selection.

Author

Markus Ulmer

Examples

set.seed(1)
n <- 10
X <- matrix(rnorm(n * 5), nrow = n)
y <- sign(X[, 1]) * 3 + sign(X[, 2]) + rnorm(n)
model <- SDTree(x = X, y = y, Q_type = 'no_deconfounding', cp = 0.5)
paths <- regPath(model)
plot(paths)

# \donttest{
plot(paths, plotly = TRUE)


# }