| emoaIndEps | R Documentation |
Functions for the computation of unary and binary measures which are useful for the evaluation of the performace of EMOAs. See the references section for literature on these indicators.
Given a set of points points, emoaIndEps computes the
unary epsilon-indicator provided a set of reference points ref.points.
The emoaIndHV function computes the hypervolume indicator
Hyp(X, R, r). Given a set of points X (points), another set of reference
points R (ref.points) (which maybe the true Pareto front) and a reference
point r (ref.point) it is defined as Hyp(X, R, r) = HV(R, r) - HV(X, r).
Function emoaIndR1, emoaIndR2 and emoaIndR3 calculate the
R1, R2 and R3 indicator respectively.
Function emoaIndMD computes the minimum distance indicator, i.e., the minimum
Euclidean distance between two points of the set points while function
emoaIndM1 determines the mean Euclidean distance between points
and points from a reference set ref.points.
Function emoaIndC calculates the coverage of the sets points (A) and
ref.points (B). This is the ratio of points in B which are dominated by
at least one solution in A.
emoaIndONVG calculates the “Overall Non-dominated Vector Generation”
indicator. Despite its complicated name it is just the number of non-dominated points
in points.
Functions emoaIndSP and emoaIndDelta calculate spacing indicators.
The former was proposed by Schott: first calculate the sum of squared distances
between minimal distancesof points to all other points and the mean of these minimal
distance. Next, normalize by the number of points minus 1 and finally calculate the
square root. In contrast, Delta-indicator
emoaIndEps(points, ref.points, ...)
emoaIndHV(points, ref.points, ref.point = NULL, ...)
emoaIndR1(
points,
ref.points,
ideal.point = NULL,
nadir.point = NULL,
lambda = NULL,
utility = "tschebycheff",
...
)
emoaIndR2(
points,
ref.points,
ideal.point = NULL,
nadir.point = NULL,
lambda = NULL,
utility = "tschebycheff",
...
)
emoaIndR3(
points,
ref.points,
ideal.point = NULL,
nadir.point = NULL,
lambda = NULL,
utility = "tschebycheff",
...
)
emoaIndMD(points, ...)
emoaIndC(points, ref.points, ...)
emoaIndM1(points, ref.points, ...)
emoaIndONVG(points, ...)
emoaIndGD(
points,
ref.points,
p = 1,
normalize = FALSE,
dist.fun = computeEuclideanDistance,
...
)
emoaIndIGD(
points,
ref.points,
p = 1,
normalize = FALSE,
dist.fun = computeEuclideanDistance,
...
)
emoaIndDeltap(
points,
ref.points,
p = 1,
normalize = FALSE,
dist.fun = computeEuclideanDistance,
...
)
emoaIndSP(points, ...)
emoaIndDelta(points, ...)
points |
[ |
ref.points |
[ |
... |
[any] |
ref.point |
[ |
ideal.point |
[ |
nadir.point |
[ |
lambda |
[ |
utility |
[ |
p |
[ |
normalize |
[ |
dist.fun |
[ |
[numeric(1)] Epsilon indicator.
Other EMOA performance assessment tools:
approximateNadirPoint(),
approximateRefPoints(),
approximateRefSets(),
computeDominanceRanking(),
makeEMOAIndicator(),
niceCellFormater(),
normalize(),
plotDistribution(),
plotFront(),
plotScatter2d(),
plotScatter3d(),
toLatex()
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