mlr (version 2.8)

plotBMRBoxplots: Create box or violin plots for a BenchmarkResult.

Description

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)

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 instead of the id in the plot. Default is TRUE.

Value

ggplot2 plot object.

See Also

Other benchmark: 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, plotPartialPredictionGGVIS, plotPartialPrediction, plotROCCurves, plotThreshVsPerfGGVIS, plotThreshVsPerf

Examples

# see benchmark