View source: R/plotCritDifferences.R
plotCritDifferences | R Documentation |
Plots a critical-differences diagram for all classifiers and a selected measure. If a baseline is selected for the Bonferroni-Dunn test, the critical difference interval will be positioned around the baseline. If not, the best performing algorithm will be chosen as baseline.
The positioning of some descriptive elements can be moved by modifying the generated data.
plotCritDifferences(obj, baseline = NULL, pretty.names = TRUE)
obj |
( |
baseline |
( |
pretty.names |
( |
ggplot2 plot object.
Janez Demsar, Statistical Comparisons of Classifiers over Multiple Data Sets, JMLR, 2006
Other plot:
createSpatialResamplingPlots()
,
plotBMRBoxplots()
,
plotBMRRanksAsBarChart()
,
plotBMRSummary()
,
plotCalibration()
,
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()
,
plotBMRBoxplots()
,
plotBMRRanksAsBarChart()
,
plotBMRSummary()
,
reduceBatchmarkResults()
# see benchmark
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