View source: R/plot.gg_beta_uvarpro.R
| plot.gg_beta_uvarpro | R Documentation |
gg_beta_uvarpro objectHorizontal 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.
## S3 method for class 'gg_beta_uvarpro'
plot(x, ...)
x |
A |
... |
Not currently used. |
A ggplot object.
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.
gg_beta_uvarpro(), gg_beta_varpro(), gg_udependent().
if (requireNamespace("varPro", quietly = TRUE)) {
set.seed(1)
o <- varPro::uvarpro(mtcars, ntree = 50)
plot(gg_beta_uvarpro(o))
}
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