visualize\(evaluate\)discrimination$curve

Generic discrimination curve from confusion artifacts

Description

Generic discrimination curve from confusion artifacts

Usage

visualize.evaluate.discrimination.curve(
  results,
  x = fpr,
  y = tpr,
  models = NULL,
  outcomes = NULL,
  show.metric = FALSE,
  metric = NULL,
  metric.label = NULL,
  facet.by = c("none", "outcome"),
  colors = NULL,
  x.label = NULL,
  y.label = NULL,
  x.limits = NULL,
  y.limits = NULL,
  title = "Discrimination Curve",
  reference.line = NULL,
  ...
)

Arguments

`results`	A `PolyGeniusEvaluation` object.
`x`	Unquoted expression resolving against confusion-artifact columns. Defaults to `fpr`.
`y`	Unquoted expression resolving against confusion-artifact columns. Defaults to `tpr`.
`models`	Optional model filter.
`outcomes`	Optional outcome filter.
`show.metric`	Whether to append a discrimination metric to legend labels.
`metric`	Optional result-row metric to show in the legend.
`metric.label`	Display label for `metric` in the legend.
`facet.by`	Faceting mode (`“none”` or `“outcome”`).
`colors`	Optional named color vector.
`x.label`	Optional x-axis label.
`y.label`	Optional y-axis label.
`x.limits`	Optional x-axis limits.
`y.limits`	Optional y-axis limits.
`title`	Plot title.
`reference.line`	Optional named list passed to `geom_abline()` with elements such as `intercept`, `slope`, `linetype`, and `color`.
`…`	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.distribution(), 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()