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()