dict_filtors_proxy | R Documentation |
Filtor that performs the operation in its operation
configuration parameter. This can be used to make filtor operations fully parametrizable.
operation
:: Filtor
Operation to perform. Must be set by the user.
This is primed when $prime()
of SelectorProxy
is called, and also when $operate()
is called, to make changing
the operation as part of self-adaption possible. However, if the same operation gets used inside multiple SelectorProxy
objects, then it is recommended to $clone(deep = TRUE)
the object before assigning them to operation
to avoid
frequent re-priming.
Supported Domain
classes are: p_lgl
('ParamLgl'), p_int
('ParamInt'), p_dbl
('ParamDbl'), p_fct
('ParamFct')
This Selector
can be created with the short access form sel()
(sels()
to get a list), or through the the dictionary
dict_selectors
in the following way:
# preferred: sel("proxy") sels("proxy") # takes vector IDs, returns list of Selectors # long form: dict_selectors$get("proxy")
miesmuschel::MiesOperator
-> miesmuschel::Filtor
-> FiltorProxy
new()
Initialize the FiltorProxy
object.
FiltorProxy$new()
prime()
See MiesOperator
method. Primes both this operator, as well as the operator given to the operation
configuration parameter.
Note that this modifies the $param_set$values$operation
object.
FiltorProxy$prime(param_set)
param_set
(ParamSet
)
Passed to MiesOperator
$prime()
.
invisible self
.
clone()
The objects of this class are cloneable with this method.
FiltorProxy$clone(deep = FALSE)
deep
Whether to make a deep clone.
Other filtors:
Filtor
,
FiltorSurrogate
,
dict_filtors_maybe
,
dict_filtors_null
,
dict_filtors_surprog
,
dict_filtors_surtour
Other filtor wrappers:
dict_filtors_maybe
library("mlr3")
library("mlr3learners")
fp = ftr("proxy")
p = ps(x = p_dbl(-5, 5))
known_data = data.frame(x = 1:5)
fitnesses = 1:5
new_data = data.frame(x = c(2.5, 4.5))
fp$param_set$values$operation = ftr("null")
fp$prime(p)
fp$operate(new_data, known_data, fitnesses, 1)
fp$param_set$values$operation = ftr("surprog", lrn("regr.lm"), filter.pool_factor = 2)
fp$operate(new_data, known_data, fitnesses, 1)
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