measure
across all iterations
of the resampling strategy, faceted by the task.id
.
plotBMRBoxplots(bmr, measure = NULL, style = "box", order.lrns = NULL, order.tsks = NULL, pretty.names = TRUE, facet.wrap.nrow = NULL, facet.wrap.ncol = NULL)
BenchmarkResult
]
Benchmark result.Measure
]
Performance measure.
Default is the first measure used in the benchmark experiment.character(1)
]
Type of plot, can be box for a boxplot or violin for a violin plot.
Default is box.character(n.learners)
]
Character vector with learner.ids
in new order.character(n.tasks)
]
Character vector with task.ids
in new order.logical(1)
]
Whether to use the Measure
name instead of the id in the plot.
Default is TRUE
.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.BenchmarkResult
,
benchmark
,
convertBMRToRankMatrix
,
friedmanPostHocTestBMR
,
friedmanTestBMR
,
generateCritDifferencesData
,
getBMRAggrPerformances
,
getBMRFeatSelResults
,
getBMRFilteredFeatures
,
getBMRLearnerIds
,
getBMRLearnerShortNames
,
getBMRLearners
,
getBMRMeasureIds
,
getBMRMeasures
, getBMRModels
,
getBMRPerformances
,
getBMRPredictions
,
getBMRTaskIds
,
getBMRTuneResults
,
plotBMRRanksAsBarChart
,
plotBMRSummary
,
plotCritDifferences
Other plot: plotBMRRanksAsBarChart
,
plotBMRSummary
,
plotCalibration
,
plotCritDifferences
,
plotFilterValuesGGVIS
,
plotFilterValues
,
plotLearningCurveGGVIS
,
plotLearningCurve
,
plotPartialDependenceGGVIS
,
plotPartialDependence
,
plotROCCurves
,
plotThreshVsPerfGGVIS
,
plotThreshVsPerf