visualize\(evaluate\)discrimination$forest

Forest plot for one evaluation metric

Description

Forest plot for one evaluation metric

Usage

visualize.evaluate.forest(
  results,
  analysis = NULL,
  metric = "auto",
  models = NULL,
  outcomes = NULL,
  sort.by = c("metric", "name", "none"),
  show.reference = TRUE,
  colors = NULL,
  ...
)

Arguments

`results`	A `PolyGeniusEvaluation` object.
`analysis`	Optional analysis filter.
`metric`	Metric name or `“auto”`.
`models`	Optional model filter.
`outcomes`	Optional outcome filter.
`sort.by`	Sorting rule (`“metric”`, `“name”`, `“none”`).
`show.reference`	Whether to draw a metric reference line when defined.
`colors`	Optional named color vector.
`…`	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.distribution(), 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()