friedmanTestBMR: Perform overall Friedman test for a BenchmarkResult.

In riebetob/mlr: Machine Learning in R

Description

Performs a friedman.test for a selected measure. The null hypothesis is that apart from an effect of the different [Task], the location parameter (aggregated performance measure) is the same for each Learner. Note that benchmark results for at least two learners on at least two tasks are required.

Usage

friedmanTestBMR(bmr, measure = NULL, aggregation = "default")

Arguments

bmr	[BenchmarkResult] Benchmark result.
measure	[Measure] Performance measure. Default is the first measure used in the benchmark experiment.
aggregation	[character(1)] “mean” or “default”. See getBMRAggrPerformances for details on “default”.

Value

[htest]: See friedman.test for details.

See Also

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

Examples

# see benchmark

riebetob/mlr documentation built on May 20, 2019, 5:58 p.m.