Feature Selection via Genetic Search
FSelectorGeneticSearch class that implements an Genetic Search. Calls
genalg::rbga.bin() from package genalg.
This FSelector can be instantiated via the dictionary
mlr_fselectors or with the associated sugar function fs():
mlr_fselectors$get("genetic_search")
fs("genetic_search")suggestionslist()
popSizeinteger(1)
mutationChancenumeric(1)
elitisminteger(1)
zeroToOneRatiointeger(1)
itersinteger(1)
For the meaning of the control parameters, see genalg::rbga.bin().
genalg::rbga.bin() internally terminates after iters iteration. We set
ìters = 100000 to allow the termination via our terminators. If more
iterations are needed, set ìters to a higher value in the parameter set.
mlr3fselect::FSelector -> FSelectorGeneticSearch
new()
Creates a new instance of this R6 class.
FSelectorGeneticSearch$new()
clone()
The objects of this class are cloneable with this method.
FSelectorGeneticSearch$clone(deep = FALSE)
deepWhether to make a deep clone.
library(mlr3)
terminator = trm("evals", n_evals = 5)
instance = FSelectInstanceSingleCrit$new(
task = tsk("iris"),
learner = lrn("classif.rpart"),
resampling = rsmp("holdout"),
measure = msr("classif.ce"),
terminator = terminator
)
fselector = fs("genetic_search", popSize = 10L)
# Modifies the instance by reference
fselector$optimize(instance)
# Returns best scoring evaluation
instance$result
# Allows access of data.table of full path of all evaluations
as.data.table(instance$archive)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.