This is a CPOConstructor
to be used to create a
CPO
. It is called like any R function and returns
the created CPO
.
Build a CPO
that represents the operations of its input parameters,
performed in parallel and put together column wise.
For example, to construct a Task
that contains the original
data, as well as the data after scaling, one could do
task %>>% cpoCbind(NULLCPO, cpoScale())
The result of cpoCbind
is itself a CPO which exports its constituents'
hyperparameters. CPOs with the same type / ID get combined automatically.
To get networks, e.g. of the form
,-C--E-. / / \ A---B----D-----F---G
one coul use the code
initcpo = A %>>% B route1 = initcpo %>>% D route2 = cpoCbind(route1, initcpo %>>% C) %>>% E result = cpoCbind(route1, route2) %>>% F %>>% G
cpoCbind
finds common paths among its arguments and combines them into one operation.
This saves computation and makes it possible for one exported hyperparameter to
influence multiple of cpoCbind
's inputs. However, if you want to use the same
operation with different parameters on different parts of cpoCbind
input,
you must give these operations different IDs. If CPOs that could represent an identical CPO,
with the same IDs (or both with IDs absent) but different parameter settings, affect.*
settings
or different parameter exportations occur, an error will be thrown.
cpoCbind(..., .cpos = list())
... | [ |
---|---|
.cpos | [ |
[CPO
].
This function creates a CPO object, which can be applied to
Task
s, data.frame
s, link{Learner}
s
and other CPO objects using the %>>%
operator.
The parameters of this object can be changed after creation
using the function setHyperPars
. The other
hyper-parameter manipulating functins, getHyperPars
and getParamSet
similarly work as one expects.
If the “id” parameter is given, the hyperparameters will have this id as aprefix; this will, however, not change the parameters of the creator function.
CPOConstructor
CPO constructor functions are called with optional values of parameters, and additional “special” optional values.
The special optional values are the id
parameter, and the affect.*
parameters. The affect.*
parameters
enable the user to control which subset of a given dataset is affected. If no affect.*
parameters are given, all
data features are affected by default.
Other CPOs:
cpoApplyFunRegrTarget()
,
cpoApplyFun()
,
cpoAsNumeric()
,
cpoCache()
,
cpoCollapseFact()
,
cpoDropConstants()
,
cpoDummyEncode()
,
cpoFilterAnova()
,
cpoFilterCarscore()
,
cpoFilterChiSquared()
,
cpoFilterFeatures()
,
cpoFilterGainRatio()
,
cpoFilterInformationGain()
,
cpoFilterKruskal()
,
cpoFilterLinearCorrelation()
,
cpoFilterMrmr()
,
cpoFilterOneR()
,
cpoFilterPermutationImportance()
,
cpoFilterRankCorrelation()
,
cpoFilterRelief()
,
cpoFilterRfCImportance()
,
cpoFilterRfImportance()
,
cpoFilterRfSRCImportance()
,
cpoFilterRfSRCMinDepth()
,
cpoFilterSymmetricalUncertainty()
,
cpoFilterUnivariate()
,
cpoFilterVariance()
,
cpoFixFactors()
,
cpoIca()
,
cpoImpactEncodeClassif()
,
cpoImpactEncodeRegr()
,
cpoImputeConstant()
,
cpoImputeHist()
,
cpoImputeLearner()
,
cpoImputeMax()
,
cpoImputeMean()
,
cpoImputeMedian()
,
cpoImputeMin()
,
cpoImputeMode()
,
cpoImputeNormal()
,
cpoImputeUniform()
,
cpoImpute()
,
cpoLogTrafoRegr()
,
cpoMakeCols()
,
cpoMissingIndicators()
,
cpoModelMatrix()
,
cpoOversample()
,
cpoPca()
,
cpoProbEncode()
,
cpoQuantileBinNumerics()
,
cpoRegrResiduals()
,
cpoResponseFromSE()
,
cpoSample()
,
cpoScaleMaxAbs()
,
cpoScaleRange()
,
cpoScale()
,
cpoSelect()
,
cpoSmote()
,
cpoSpatialSign()
,
cpoTransformParams()
,
cpoWrap()
,
makeCPOCase()
,
makeCPOMultiplex()
Other special CPOs:
cpoTransformParams()
,
cpoWrap()
,
makeCPOCase()
,
makeCPOMultiplex()