Visualizes of empirical distributions of unary EMOA indicator
based on the results of computeIndicators.
plotDistribution(
inds,
plot.type = "boxplot",
fill = "algorithm",
facet.type = "grid",
facet.args = list(),
logscale = character()
)[ggplot]
[data.frame]
Data frame with columns “algorithm”, “prob”, “repl” and
one additional column per EMOA indicator.
[character(1)]
Either “boxplot” (the default) for boxplots or “violin” for
violin plots.
[character(1)]
Variable used to fill boxplots.
Default is “algorithm”.
[character(1)]
Which faceting method to use? Pass “wrap” for facet_wrap
or “grid” for facet_grid.
Default is “wrap”.
[list]
Named list of arguments passed down to facet_wrap or
facet_grid respectively (depends on facet.type).
E.g., nrow to change layout.
Default is the empty list. In this case data is grouped by problem and indicator.
[character]
Vector of indicator names which should be log-transformed prior to
visualization.
Default is the empty character vector.
Other EMOA performance assessment tools:
approximateNadirPoint(),
approximateRefPoints(),
approximateRefSets(),
computeDominanceRanking(),
emoaIndEps(),
makeEMOAIndicator(),
niceCellFormater(),
normalize(),
plotFront(),
plotScatter2d(),
plotScatter3d(),
toLatex()