mlr: plotThreshVsPerf – R documentation

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mlr

plotThreshVsPerf

Plot threshold vs. performance(s) for 2-class classification using ggplot2.

Description

Plots threshold vs. performance(s) data that has been generated with generateThreshVsPerfData.

Usage

plotThreshVsPerf(
  obj,
  measures = obj$measures,
  facet = "measure",
  mark.th = NA_real_,
  pretty.names = TRUE,
  facet.wrap.nrow = NULL,
  facet.wrap.ncol = NULL
)

Arguments

`obj`	(ThreshVsPerfData) Result of generateThreshVsPerfData.
`measures`	(Measure \| list of Measure) Performance measure(s) to plot. Must be a subset of those used in generateThreshVsPerfData. Default is all the measures stored in `obj` generated by generateThreshVsPerfData.
`facet`	(`character(1)`) Selects “measure” or “learner” to be the facetting variable. The variable mapped to `facet` must have more than one unique value, otherwise it will be ignored. The variable not chosen is mapped to color if it has more than one unique value. The default is “measure”.
`mark.th`	(`numeric(1)`) Mark given threshold with vertical line? Default is `NA` which means not to do it.
`pretty.names`	(`logical(1)`) Whether to use the Measure name instead of the id in the plot. Default is `TRUE`.
`facet.wrap.nrow, facet.wrap.ncol`	(integer) Number of rows and columns for facetting. Default for both is `NULL`. In this case ggplot's `facet_wrap` will choose the layout itself.

Value

ggplot2 plot object.

Examples

lrn = makeLearner("classif.rpart", predict.type = "prob")
mod = train(lrn, sonar.task)
pred = predict(mod, sonar.task)
pvs = generateThreshVsPerfData(pred, list(acc, setAggregation(acc, train.mean)))
plotThreshVsPerf(pvs)

mlr

Machine Learning in R

v2.19.0

BSD_2_clause + file LICENSE

Authors

Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>), Michel Lang [aut] (<https://orcid.org/0000-0001-9754-0393>), Lars Kotthoff [aut], Patrick Schratz [aut, cre] (<https://orcid.org/0000-0003-0748-6624>), Julia Schiffner [aut], Jakob Richter [aut], Zachary Jones [aut], Giuseppe Casalicchio [aut] (<https://orcid.org/0000-0001-5324-5966>), Mason Gallo [aut], Jakob Bossek [ctb] (<https://orcid.org/0000-0002-4121-4668>), Erich Studerus [ctb] (<https://orcid.org/0000-0003-4233-0182>), Leonard Judt [ctb], Tobias Kuehn [ctb], Pascal Kerschke [ctb] (<https://orcid.org/0000-0003-2862-1418>), Florian Fendt [ctb], Philipp Probst [ctb] (<https://orcid.org/0000-0001-8402-6790>), Xudong Sun [ctb] (<https://orcid.org/0000-0003-3269-2307>), Janek Thomas [ctb] (<https://orcid.org/0000-0003-4511-6245>), Bruno Vieira [ctb], Laura Beggel [ctb] (<https://orcid.org/0000-0002-8872-8535>), Quay Au [ctb] (<https://orcid.org/0000-0002-5252-8902>), Martin Binder [ctb], Florian Pfisterer [ctb], Stefan Coors [ctb], Steve Bronder [ctb], Alexander Engelhardt [ctb], Christoph Molnar [ctb], Annette Spooner [ctb]

Initial release