Plots box or violin plots for a selected measure
across all iterations
of the resampling strategy, faceted by the task.id
.
Usage
plotBMRBoxplots(
bmr,
measure = NULL,
style = "box",
order.lrns = NULL,
order.tsks = NULL,
pretty.names = TRUE,
facet.wrap.nrow = NULL,
facet.wrap.ncol = NULL
)
Arguments
- bmr
(BenchmarkResult)
Benchmark result.- measure
(Measure)
Performance measure. Default is the first measure used in the benchmark experiment.- style
(
character(1)
)
Type of plot, can be “box” for a boxplot or “violin” for a violin plot. Default is “box”.- order.lrns
(
character(n.learners)
)
Character vector withlearner.ids
in new order.- order.tsks
(
character(n.tasks)
)
Character vector withtask.ids
in new order.- pretty.names
(
logical(1)
)
Whether to use the Measure name and the Learner short name instead of the id. Default isTRUE
.- facet.wrap.nrow, facet.wrap.ncol
(integer)
Number of rows and columns for facetting. Default for both isNULL
. In this case ggplot'sfacet_wrap
will choose the layout itself.
See also
Other plot:
createSpatialResamplingPlots()
,
plotBMRRanksAsBarChart()
,
plotBMRSummary()
,
plotCalibration()
,
plotCritDifferences()
,
plotLearningCurve()
,
plotPartialDependence()
,
plotROCCurves()
,
plotResiduals()
,
plotThreshVsPerf()
Other benchmark:
BenchmarkResult
,
batchmark()
,
benchmark()
,
convertBMRToRankMatrix()
,
friedmanPostHocTestBMR()
,
friedmanTestBMR()
,
generateCritDifferencesData()
,
getBMRAggrPerformances()
,
getBMRFeatSelResults()
,
getBMRFilteredFeatures()
,
getBMRLearnerIds()
,
getBMRLearnerShortNames()
,
getBMRLearners()
,
getBMRMeasureIds()
,
getBMRMeasures()
,
getBMRModels()
,
getBMRPerformances()
,
getBMRPredictions()
,
getBMRTaskDescs()
,
getBMRTaskIds()
,
getBMRTuneResults()
,
plotBMRRanksAsBarChart()
,
plotBMRSummary()
,
plotCritDifferences()
,
reduceBatchmarkResults()