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Plots threshold vs. performance(s) data that has been generated with generateThreshVsPerfData.
plotThreshVsPerf(obj, measures = obj$measures, facet = "measure",
mark.th = NA_real_, pretty.names = TRUE, facet.wrap.nrow = NULL,
facet.wrap.ncol = NULL)
(ThreshVsPerfData) Result of generateThreshVsPerfData.
(Measure | list of Measure)
Performance measure(s) to plot.
Must be a subset of those used in generateThreshVsPerfData.
Default is all the measures stored in obj
generated by
generateThreshVsPerfData.
(character(1)
)
Selects “measure” or “learner” to be the facetting variable.
The variable mapped to facet
must have more than one unique value, otherwise it will
be ignored. The variable not chosen is mapped to color if it has more than one unique value.
The default is “measure”.
(numeric(1)
)
Mark given threshold with vertical line?
Default is NA
which means not to do it.
(logical(1)
)
Whether to use the Measure name instead of the id in the plot.
Default is TRUE
.
(integer)
Number of rows and columns for facetting. Default for both is NULL
.
In this case ggplot's facet_wrap
will choose the layout itself.
ggplot2 plot object.
Other plot: createSpatialResamplingPlots
,
plotBMRBoxplots
,
plotBMRRanksAsBarChart
,
plotBMRSummary
,
plotCalibration
,
plotCritDifferences
,
plotLearningCurve
,
plotPartialDependence
,
plotROCCurves
, plotResiduals
Other thresh_vs_perf: generateThreshVsPerfData
,
plotROCCurves
# NOT RUN {
lrn = makeLearner("classif.rpart", predict.type = "prob")
mod = train(lrn, sonar.task)
pred = predict(mod, sonar.task)
pvs = generateThreshVsPerfData(pred, list(acc, setAggregation(acc, train.mean)))
plotThreshVsPerf(pvs)
# }
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