E.g., for calculation of dominated hypervolume.
approximateRefPoints(df, obj.cols = c("f1", "f2"), offset = 0, as.df = FALSE)
[list
| data.frame
]
[data.frame
]
Data frame with the required structure, i.e. the data frame must contain a problem column "prob" as well as objective column(s).
[character(>= 2)
]
Column names of the objective functions.
Default is c("f1", "f2")
, i.e., the bi-objective case is assumed.
[numeric(1)
]
Offset added to reference points.
Default is 0
.
[logical(1)
]
Should a data.frame be returned?
Default is FALSE
. In this case a named list is returned.
Other EMOA performance assessment tools:
approximateNadirPoint()
,
approximateRefSets()
,
computeDominanceRanking()
,
emoaIndEps()
,
makeEMOAIndicator()
,
niceCellFormater()
,
normalize()
,
plotDistribution()
,
plotFront()
,
plotScatter2d()
,
plotScatter3d()
,
toLatex()