mlr (version 2.6)

plotCritDifferences: Plot critical differences for a selected measure.

Description

Plots a critical-differences diagram for all classifiers and a selected measure. If a baseline is selected for the Bonferroni-Dunn test, the critical difference interval will be positioned arround the baseline. If not, the best performing algorithm will be chosen as baseline.

Usage

plotCritDifferences(obj, baseline = NULL)

Value

ggplot2 plot object.

References

Janez Demsar, Statistical Comparisons of Classifiers over Multiple Data Sets, JMLR, 2006

See Also

Other benchmark: BenchmarkResult, benchmark, convertBMRToRankMatrix, friedmanPostHocTestBMR, friedmanTestBMR, generateBenchmarkSummaryData, generateCritDifferencesData, generateRankMatrixAsBarData, getBMRAggrPerformances, getBMRFeatSelResults, getBMRFilteredFeatures, getBMRLearnerIds, getBMRLearners, getBMRMeasureIds, getBMRMeasures, getBMRPerformances, getBMRPredictions, getBMRTaskIds, getBMRTuneResults, plotBenchmarkResult, plotBenchmarkSummary, plotRankMatrixAsBar

Other plot: plotBenchmarkResult, plotBenchmarkSummary, plotCalibration, plotFilterValuesGGVIS, plotFilterValues, plotLearningCurveGGVIS, plotLearningCurve, plotPartialPredictionGGVIS, plotPartialPrediction, plotROCCurves, plotROCRCurvesGGVIS, plotROCRCurves, plotRankMatrixAsBar, plotThreshVsPerfGGVIS, plotThreshVsPerf

Examples

lrns = list(makeLearner("classif.nnet"), makeLearner("classif.rpart"))
tasks = list(iris.task, sonar.task)
rdesc = makeResampleDesc("CV", iters = 2L)
meas = list(acc, mmce)
res = benchmark(lrns, tasks, rdesc, meas)
r = generateCritDifferencesData(res, mmce, p.value = 0.3, test = "bd")
plotCritDifferences(r)