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