plotLearningCurveGGVIS: Plot learning curve data using ggvis.

In riebetob/mlr: Machine Learning in R

Description

Visualizes data size (percentage used for model) vs. performance measure(s).

Usage

plotLearningCurveGGVIS(obj, interaction = "measure", pretty.names = TRUE)

Arguments

obj	[LearningCurveData] Result of generateLearningCurveData.
interaction	[character(1)] Selects “measure” or “learner” to be used in a Shiny application making the interaction variable selectable via a drop-down menu. This variable 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. Note that if there are multiple learners and multiple measures interactivity is necessary as ggvis does not currently support facetting or subplots. The default is “measure”.
pretty.names	[logical(1)] Whether to use the Measure name instead of the id in the plot. Default is TRUE.

Value

a ggvis plot object.

See Also

Other plot: plotBMRBoxplots, plotBMRRanksAsBarChart, plotBMRSummary, plotCalibration, plotCritDifferences, plotFilterValuesGGVIS, plotLearningCurve, plotPartialDependenceGGVIS, plotPartialDependence, plotROCCurves, plotResiduals, plotThreshVsPerfGGVIS, plotThreshVsPerf

Other learning_curve: generateLearningCurveData, plotLearningCurve

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