| dict_filtors_proxy {miesmuschel} | R Documentation | 
Proxy-Filtor that Filters According to its Configuration Parameter
Description
Filtor that performs the operation in its operation configuration parameter. This can be used to make filtor operations fully parametrizable.
Configuration Parameters
-  
operation::Filtor
Operation to perform. Must be set by the user. This is primed when$prime()ofSelectorProxyis called, and also when$operate()is called, to make changing the operation as part of self-adaption possible. However, if the same operation gets used inside multipleSelectorProxyobjects, then it is recommended to$clone(deep = TRUE)the object before assigning them tooperationto avoid frequent re-priming. 
Supported Operand Types
Supported Domain classes are: p_lgl ('ParamLgl'), p_int ('ParamInt'), p_dbl ('ParamDbl'), p_fct ('ParamFct')
Dictionary
This Selector can be created with the short access form sel()
(sels() to get a list), or through the the dictionary
dict_selectors in the following way:
# preferred:
sel("proxy")
sels("proxy")  # takes vector IDs, returns list of Selectors
# long form:
dict_selectors$get("proxy")
Super classes
miesmuschel::MiesOperator -> miesmuschel::Filtor -> FiltorProxy
Methods
Public methods
Inherited methods
Method new()
Initialize the FiltorProxy object.
Usage
FiltorProxy$new()
Method 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$operation object.
Usage
FiltorProxy$prime(param_set)
Arguments
param_set(
ParamSet)
Passed toMiesOperator$prime().
Returns
invisible self.
Method clone()
The objects of this class are cloneable with this method.
Usage
FiltorProxy$clone(deep = FALSE)
Arguments
deepWhether to make a deep clone.
See Also
Other filtors: 
Filtor,
FiltorSurrogate,
dict_filtors_maybe,
dict_filtors_null,
dict_filtors_surprog,
dict_filtors_surtour
Other filtor wrappers: 
dict_filtors_maybe
Examples
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)