Skip to contents

Plot a gg_beta_uvarpro object

Source: R/plot.gg_beta_uvarpro.R
plot.gg_beta_uvarpro.Rd

Horizontal bar chart of the mean absolute lasso coefficient \(\mathrm{mean}(|\hat{\beta}|)\) per variable from an unsupervised varPro fit, sorted descending so the eye lands on the top variable first. Bars are filled blue above the selection cutoff, gray otherwise, with a dashed red line at the cutoff.

Usage

# S3 method for class 'gg_beta_uvarpro'
plot(x, labels = NULL, ...)

Arguments

x

A gg_beta_uvarpro object from gg_beta_uvarpro().

labels

Optional variable labels for the variable axis. One of: a named character vector (c(wt = "Weight")); a labelled data frame, whose attr(col, "label") values are read; or a two-column key/label data frame. Variables with no label keep their raw name. Defaults to NULL (raw names).

...

Not currently used.

Value

A ggplot object.

Reading the chart

Each bar is the average magnitude of a per-region lasso coefficient for that variable, computed by varPro::get.beta.entropy() over the unsupervised entropy regions of a varPro::uvarpro() fit. There is no response: the score measures how strongly a variable is reconstructed by the others within released regions, i.e. an unsupervised importance / redundancy signal rather than a predictive one. As with gg_beta_varpro(), the numeric scale carries the predictors' units, so bar lengths are comparable within a data set but not blindly across variables on very different scales.

See also

gg_beta_uvarpro(), gg_beta_varpro(), gg_udependent().

Examples

# \donttest{
if (requireNamespace("varPro", quietly = TRUE)) {
  set.seed(1)
  o <- varPro::uvarpro(mtcars, ntree = 50)
  plot(gg_beta_uvarpro(o))
}

# }