mlr (version 2.8)

plotPartialPrediction: Plot a partial prediction with ggplot2.

Description

Plot a partial prediction from generatePartialPredictionData using ggplot2.

Usage

plotPartialPrediction(obj, geom = "line", facet = NULL, p = 1)

Arguments

obj

[PartialPredictionData] Generated by generatePartialPredictionData.

geom

[charater(1)] The type of geom to use to display the data. Can be “line” or “tile”. For tiling at least two features must be used with interaction = TRUE in the call to generatePartialPredictionData. This may be used in conjuction with the facet argument if three features are specified in the call to generatePartialPredictionData. Default is “line”.

facet

[character(1)] The name of a feature to be used for facetting. This feature must have been an element of the features argument to generatePartialPredictionData and is only applicable when said argument had length greater than 1. If generatePartialPredictionData is called with the interaction argument FALSE (the default) with argument features of length greater than one, then facet is ignored and each feature is plotted in its own facet. Note that if any of the elements of the features argument of generatePartialPredictionData are factors, they will be coerced to numerics. Default is NULL.

p

[numeric(1)] If individual = TRUE then sample allows the user to sample without replacement from the output to make the display more readable. Each row is sampled with probability p. Default is 1.

Value

ggplot2 plot object.

See Also

Other partial_prediction: generatePartialPredictionData, plotPartialPredictionGGVIS

Other plot: plotBMRBoxplots, plotBMRRanksAsBarChart, plotBMRSummary, plotCalibration, plotCritDifferences, plotFilterValuesGGVIS, plotFilterValues, plotLearningCurveGGVIS, plotLearningCurve, plotPartialPredictionGGVIS, plotROCCurves, plotThreshVsPerfGGVIS, plotThreshVsPerf