Description Usage Arguments Value See Also
View source: R/plotCritDifferences.R
Generates data that can be used to plot a
critical differences plot. Computes the critical differences according
to either the
"BonferroniDunn"
test or the "Nemenyi"
test.
"BonferroniDunn"
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 yaxis 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 baseline. All learners within this interval are not signifcantly different
from the baseline.
Calculation:
CD = q_alpha sqrt(k(k+1)/(6N))
Where q_α is based on the studentized range statistic.
See references for details.
1 2  generateCritDifferencesData(bmr, measure = NULL, p.value = 0.05,
baseline = NULL, test = "bd")

bmr 
[ 
measure 
[ 
p.value 
[ 
baseline 
[ 
test 
[ 
[critDifferencesData
]. List containing:
data 
[ 
friedman.nemenyi.test 
[ 
cd.info 
[ 
baseline 

p.value 
p.value used for the posthoc.friedman.nemenyi.test and for computation of the critical difference 
Other generate_plot_data: generateCalibrationData
,
generateFeatureImportanceData
,
generateFilterValuesData
,
generateFunctionalANOVAData
,
generateLearningCurveData
,
generatePartialDependenceData
,
generateThreshVsPerfData
,
getFilterValues
,
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
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