generateCritDifferencesData: Generate data for critical-differences plot.

View source: R/plotCritDifferences.R

generateCritDifferencesDataR Documentation

Generate data for critical-differences plot.


Generates data that can be used to plot a critical differences plot. Computes the critical differences according to either the "Bonferroni-Dunn" test or the "Nemenyi" test.
"Bonferroni-Dunn" usually yields higher power as it does not compare all algorithms to each other, but all algorithms to a baseline instead.
Learners are drawn on the y-axis according to their average rank.
For test = "nemenyi" a bar is drawn, connecting all groups of not significantly different learners.
For test = "bd" an interval is drawn arround the algorithm selected as a baseline. All learners within this interval are not signifcantly different from the baseline.

CD = q_alpha sqrt(k(k+1)/(6N))

Where q_α is based on the studentized range statistic. See references for details.


  measure = NULL,
  p.value = 0.05,
  baseline = NULL,
  test = "bd"



Benchmark result.


Performance measure. Default is the first measure used in the benchmark experiment.


P-value for the critical difference. Default: 0.05


(character(1)): (
Select a as baseline for the test = "bd" ("Bonferroni-Dunn") critical differences diagram. The critical difference interval will then be positioned arround this learner. Defaults to best performing algorithm.
For test = "nemenyi", no baseline is needed as it performs all pairwise comparisons.


Test for which the critical differences are computed.
“bd” for the Bonferroni-Dunn Test, which is comparing all classifiers to a baseline, thus performing a comparison of one classifier to all others.
Algorithms not connected by a single line are statistically different from the baseline.
“nemenyi” for the PMCMRplus::frdAllPairsNemenyiTest which is comparing all classifiers to each other. The null hypothesis that there is a difference between the classifiers can not be rejected for all classifiers that have a single grey bar connecting them.


(critDifferencesData). List containing:


(data.frame) containing the info for the descriptive part of the plot


(list) of class pairwise.htest
contains the calculated PMCMRplus::frdAllPairsNemenyiTest

(list) containing info on the critical difference and its positioning


baseline chosen for plotting


p.value used for the PMCMRplus::frdAllPairsNemenyiTest and for computation of the critical difference

See Also

Other generate_plot_data: generateCalibrationData(), generateFeatureImportanceData(), generateFilterValuesData(), generateLearningCurveData(), generatePartialDependenceData(), generateThreshVsPerfData(), plotFilterValues()

Other benchmark: BenchmarkResult, batchmark(), benchmark(), convertBMRToRankMatrix(), friedmanPostHocTestBMR(), friedmanTestBMR(), getBMRAggrPerformances(), getBMRFeatSelResults(), getBMRFilteredFeatures(), getBMRLearnerIds(), getBMRLearnerShortNames(), getBMRLearners(), getBMRMeasureIds(), getBMRMeasures(), getBMRModels(), getBMRPerformances(), getBMRPredictions(), getBMRTaskDescs(), getBMRTaskIds(), getBMRTuneResults(), plotBMRBoxplots(), plotBMRRanksAsBarChart(), plotBMRSummary(), plotCritDifferences(), reduceBatchmarkResults()

mlr documentation built on Sept. 29, 2022, 5:05 p.m.