plotBMRBoxplots: Create box or violin plots for a BenchmarkResult.

Description Usage Arguments Value See Also Examples

View source: R/plotBMRBoxplots.R

Description

Plots box or violin plots for a selected measure across all iterations of the resampling strategy, faceted by the task.id.

Usage

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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 with learner.ids in new order.

order.tsks

[character(n.tasks)]
Character vector with task.ids in new order.

pretty.names

[logical(1)]
Whether to use the Measure name and the Learner short name instead of the id. 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.

See Also

Other plot: plotBMRRanksAsBarChart, plotBMRSummary, plotCalibration, plotCritDifferences, plotFilterValuesGGVIS, plotLearningCurveGGVIS, plotLearningCurve, plotPartialDependenceGGVIS, plotPartialDependence, plotROCCurves, plotResiduals, plotThreshVsPerfGGVIS, 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

Examples

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# see benchmark

berndbischl/mlr documentation built on Dec. 12, 2017, 8:28 p.m.