register_GA | R Documentation |
Register a GA-based seriation metaheuristic for use with seriate()
.
register_GA()
gaperm_mixedMutation(ismProb = 0.8)
ismProb |
probability to use |
Registers the method "GA"
for seriate()
. This method can be used
to optimize any criterion in package seriation.
The GA uses by default the ordered cross-over (OX) operator. For mutation,
the GA uses a mixture of simple insertion and simple inversion operators.
This mixed operator is created using
seriation::gaperm_mixedMutation(ismProb = .8)
, where ismProb
is the probability that the simple insertion mutation operator is used. See
package GA for a description of other available cross-over and
mutation operators for permutations. The appropriate operator functions in
GA start with gaperm_
.
We warm start the GA using "suggestions"
given by several heuristics.
Set "suggestions"
to NA
to start with a purely random initial
population.
See Example section for available control parameters.
Note: Package GA needs to be installed.
Nothing.
Michael Hahsler
Luca Scrucca (2013): GA: A Package for Genetic Algorithms in R. Journal of Statistical Software, 53(4), 1–37. URL \Sexpr[results=rd]{tools:::Rd_expr_doi("10.18637/jss.v053.i04")}.
Other seriation:
register_DendSer()
,
register_optics()
,
register_smacof()
,
register_tsne()
,
register_umap()
,
registry_for_seriaiton_methods
,
seriate()
,
seriate_best()
## Not run:
register_GA()
get_seriation_method("dist", "GA")
data(SupremeCourt)
d <- as.dist(SupremeCourt)
## optimize for linear seriation criterion (LS)
o <- seriate(d, "GA", criterion = "LS", verbose = TRUE)
pimage(d, o)
## Note that by default the algorithm is already seeded with a LS heuristic.
## This run is no warm start (no suggestions) and increase run to 100
o <- seriate(d, "GA", criterion = "LS", suggestions = NA, run = 100,
verbose = TRUE)
pimage(d, o)
o <- seriate(d, "GA", criterion = "LS", suggestions = NA, run = 100,
verbose = TRUE, )
pimage(d, o)
## End(Not run)
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