visualize\(evaluate\)similarity$heatmap

Similarity heatmap for evaluation results

Description

Similarity heatmap for evaluation results

Usage

visualize.evaluate.similarity.heatmap(
  results,
  models = NULL,
  cluster = TRUE,
  cols = colorRampPalette(c("darkgreen", "white", "darkorchid4")),
  n.breaks = 11L,
  symmetrize.range = FALSE,
  center.zero = FALSE,
  drop.na = TRUE,
  ...
)

Arguments

`results`	A `PolyGeniusEvaluation` object containing a similarity matrix artifact, typically from `evaluate$similarity()` or from a merged evaluation object that retains that artifact.
`models`	Optional model filter.
`cluster`	Logical; whether to cluster rows and columns.
`cols`	Color palette function.
`n.breaks`	Integer number of color breaks sampled from `cols`.
`symmetrize.range`	Logical; whether to force a symmetric color range.
`center.zero`	Logical; whether to center the color scale at zero.
`drop.na`	Logical; whether to drop rows and columns that are entirely `NA`.
`…`	Additional arguments passed to `ComplexHeatmap::Heatmap()`.

Value

A ComplexHeatmap::Heatmap 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.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()