posthoc.friedman.nemenyi.test for a
BenchmarkResult and a selected measure.
This means all pairwise comparisons of learners are performed.
The null hypothesis of the post hoc test is that each pair of learners is equal.
If the null hypothesis of the included ad hoc friedman.test
can be rejected a pairwise.htest is returned. If not, the function returns the
corresponding friedman.test
friedmanPostHocTestBMR(bmr, measure = NULL, p.value = 0.05, aggregation = "default")BenchmarkResult]
Benchmark result.Measure]
Performance measure.
Default is the first measure used in the benchmark experiment.numeric(1)]
p-value for the tests. Default: 0.05character(1)]
“mean” or “default”. See getBMRAggrPerformances
for details on “default”.pairwise.htest]: See posthoc.friedman.nemenyi.test for details.
Additionally two components are added to the list:
BenchmarkResult,
benchmark,
convertBMRToRankMatrix,
friedmanTestBMR,
generateCritDifferencesData,
getBMRAggrPerformances,
getBMRFeatSelResults,
getBMRFilteredFeatures,
getBMRLearnerIds,
getBMRLearnerShortNames,
getBMRLearners,
getBMRMeasureIds,
getBMRMeasures, getBMRModels,
getBMRPerformances,
getBMRPredictions,
getBMRTaskIds,
getBMRTuneResults,
plotBMRBoxplots,
plotBMRRanksAsBarChart,
plotBMRSummary,
plotCritDifferences