visualize\(evaluate\)discrimination$distribution

Distribution plots from discrimination artifacts

Description

Distribution plots from discrimination artifacts

Usage

visualize.evaluate.distribution(
  results,
  models = NULL,
  outcomes = NULL,
  type = c("density", "violin", "boxplot", "histogram"),
  facet.by = c("model", "outcome", "none"),
  color.by = c("auto", "model", "group"),
  show.points = FALSE,
  raster = FALSE,
  show.outliers = TRUE,
  pattern.args = list(),
  geom.args = list(),
  raster.args = list(),
  facet.args = list(),
  ...
)

Arguments

`results`	A `PolyGeniusEvaluation` object.
`models`	Optional model filter.
`outcomes`	Optional outcome filter.
`type`	Distribution geometry (`“density”`, `“violin”`, `“boxplot”`, `“histogram”`).
`facet.by`	Faceting mode (`“model”`, `“outcome”`, `“none”`).
`color.by`	Color assignment (`“auto”`, `“model”`, or `“group”`). With `facet.by = “model”`, `“auto”` resolves to `“group”` and disables pattern encoding by default.
`show.points`	Whether to overlay points when supported.
`raster`	Whether to rasterize points.
`show.outliers`	Whether to show outliers for boxplots.
`pattern.args`	Pattern customization passed to shared score plotting backend.
`geom.args`	Geometry customization passed to shared score plotting backend.
`raster.args`	Raster customization passed to shared score plotting backend.
`facet.args`	Facet customization passed to shared score plotting backend.
`…`	Reserved for future extensions.

Value

A ggplot object.

See Also

Other visualize: visualize.evaluate.calibration.curve(), visualize.evaluate.calibration.slope.intercept(), visualize.evaluate.compare.delta.forest(), visualize.evaluate.compare.delta.heatmap(), visualize.evaluate.confusion(), visualize.evaluate.discrimination.curve(), visualize.evaluate.forest(), visualize.evaluate.incremental.delta(), visualize.evaluate.leaderboard(), visualize.evaluate.metric.flags(), visualize.evaluate.metric.heatmap(), visualize.evaluate.pr(), visualize.evaluate.predicted.vs.observed(), visualize.evaluate.residuals(), visualize.evaluate.risk.strata.lift(), visualize.evaluate.risk.strata.profile(), visualize.evaluate.roc(), visualize.evaluate.similarity.heatmap()