plotTuneMultiCritResult: Plots multi-criteria results after tuning using ggplot2.

In riebetob/mlr: Machine Learning in R

Description

Visualizes the pareto front and possibly the dominated points.

Usage

plotTuneMultiCritResult(res, path = TRUE, col = NULL, shape = NULL,
  pointsize = 2, pretty.names = TRUE)

Arguments

res	[TuneMultiCritResult] Result of tuneParamsMultiCrit.
path	[logical(1)] Visualize all evaluated points (or only the non-dominated pareto front)? For the full path, the size of the points on the front is slightly increased. Default is TRUE.
col	[character(1)] Which column of res$opt.path should be mapped to ggplot2 color? Default is NULL, which means none.
shape	[character(1)] Which column of res$opt.path should be mapped to ggplot2 shape? Default is NULL, which means none.
pointsize	[numeric(1)] Point size for ggplot2 geom_point for data points. Default is 2.
pretty.names	[logical{1}] Whether to use the ID of the measures instead of their name in labels. Defaults to TRUE.

Value

ggplot2 plot object.

See Also

Other tune_multicrit: TuneMultiCritControl, plotTuneMultiCritResultGGVIS, tuneParamsMultiCrit

Examples

# see tuneParamsMultiCrit

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