Plot threshold vs. performance(s) for 2-class classification using ggplot2.
Source:R/generateThreshVsPerf.R
plotThreshVsPerf.Rd
Plots threshold vs. performance(s) data that has been generated with generateThreshVsPerfData.
Usage
plotThreshVsPerf(
obj,
measures = obj$measures,
facet = "measure",
mark.th = NA_real_,
pretty.names = TRUE,
facet.wrap.nrow = NULL,
facet.wrap.ncol = NULL
)
Arguments
- obj
(ThreshVsPerfData)
Result of generateThreshVsPerfData.- measures
(Measure | list of Measure)
Performance measure(s) to plot. Must be a subset of those used in generateThreshVsPerfData. Default is all the measures stored inobj
generated by generateThreshVsPerfData.- facet
(
character(1)
)
Selects “measure” or “learner” to be the facetting variable. The variable mapped tofacet
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”.- mark.th
(
numeric(1)
)
Mark given threshold with vertical line? Default isNA
which means not to do it.- pretty.names
(
logical(1)
)
Whether to use the Measure name instead of the id in the plot. Default isTRUE
.- facet.wrap.nrow, facet.wrap.ncol
(integer)
Number of rows and columns for facetting. Default for both isNULL
. In this case ggplot'sfacet_wrap
will choose the layout itself.
See also
Other plot:
createSpatialResamplingPlots()
,
plotBMRBoxplots()
,
plotBMRRanksAsBarChart()
,
plotBMRSummary()
,
plotCalibration()
,
plotCritDifferences()
,
plotLearningCurve()
,
plotPartialDependence()
,
plotROCCurves()
,
plotResiduals()
Other thresh_vs_perf:
generateThreshVsPerfData()
,
plotROCCurves()
Examples
lrn = makeLearner("classif.rpart", predict.type = "prob")
mod = train(lrn, sonar.task)
#> Error in x[0, , drop = FALSE]: incorrect number of dimensions
pred = predict(mod, sonar.task)
#> Error in predict(mod, sonar.task): object 'mod' not found
pvs = generateThreshVsPerfData(pred, list(acc, setAggregation(acc, train.mean)))
#> Error in generateThreshVsPerfData(pred, list(acc, setAggregation(acc, train.mean))): object 'pred' not found
plotThreshVsPerf(pvs)
#> Error in checkClass(x, classes, ordered, null.ok): object 'pvs' not found