whv_hype | R Documentation |
Return an estimation of the hypervolume of the space dominated by the input data following the procedure described by \citetAugBadBroZit2009gecco. A weight distribution describing user preferences may be specified.
whv_hype(
data,
reference,
ideal,
maximise = FALSE,
dist = list(type = "uniform"),
nsamples = 100000L
)
data |
( |
reference |
( |
ideal |
( |
maximise |
( |
dist |
( |
nsamples |
( |
The current implementation only supports 2 objectives.
A weight distribution \citepAugBadBroZit2009gecco can be provided via the dist
argument. The ones currently supported are:
type="uniform"
corresponds to the default hypervolume (unweighted).
type="point"
describes a goal in the objective space, where mu
gives the coordinates of the goal. The resulting weight distribution is a multivariate normal distribution centred at the goal.
type="exponential"
describes an exponential distribution with rate parameter 1/mu
, i.e., \lambda = \frac{1}{\mu}
.
A single numerical value.
read_datasets()
, eafdiff()
, whv_rect()
whv_hype (matrix(2, ncol=2), reference = 4, ideal = 1)
whv_hype (matrix(c(3,1), ncol=2), reference = 4, ideal = 1)
whv_hype (matrix(2, ncol=2), reference = 4, ideal = 1,
dist = list(type="exponential", mu=0.2))
whv_hype (matrix(c(3,1), ncol=2), reference = 4, ideal = 1,
dist = list(type="exponential", mu=0.2))
whv_hype (matrix(2, ncol=2), reference = 4, ideal = 1,
dist = list(type="point", mu=c(1,1)))
whv_hype (matrix(c(3,1), ncol=2), reference = 4, ideal = 1,
dist = list(type="point", mu=c(1,1)))
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