plot.paths | R Documentation |
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, ...)
x |
A |
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. |
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.
Markus Ulmer
regPath
stabilitySelection
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)
plot(paths, plotly = TRUE)
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