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.
Calculation: $$CD = q_{\alpha} \sqrt{\left(\frac{k(k+1)}{6N}\right)}$$
Where $$q_\alpha$$ is based on the studentized range statistic. See references for details.

generateCritDifferencesData(bmr, measure = NULL, p.value = 0.05,
baseline = NULL, test = "bd")

## Arguments

bmr (BenchmarkResult) Benchmark result. (Measure) Performance measure. Default is the first measure used in the benchmark experiment. (numeric(1)) P-value for the critical difference. Default: 0.05 (character(1)): (learner.id) Select a learner.id 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. (character(1)) 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 PMCMR::posthoc.friedman.nemenyi.test 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.

## Value

(critDifferencesData). List containing:

data

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

friedman.nemenyi.test

(list) of class pairwise.htest
contains the calculated PMCMR::posthoc.friedman.nemenyi.test

cd.info

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

baseline

baseline chosen for plotting

p.value

p.value used for the PMCMR::posthoc.friedman.nemenyi.test and for computation of the critical difference

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