cpoMakeCols {mlrCPO} | R Documentation |
Create Columns from Expressions
Description
This is a CPOConstructor
to be used to create a
CPO
. It is called like any R function and returns
the created CPO
.
Create columns from expressions and the incoming data.
When cpoMakeCols
or cpoAddCols
are called as
cpoMakeCols( <newcolname> = <expression>, ... )
, a new column
with the name <newcolname
containing the result of
<expression>
is created. The
expressions need to be vectorising R expressions
and may refer to any feature columns in the data (excluding the
target) and any other values. The names should be valid data.frame
column names and may not clash with the target column name.
cpoMakeCols
replaces existing cols by the newly created
ones, cpoAddCols
adds them to the data already present.
Usage
cpoMakeCols(..., .make.factors = TRUE)
cpoAddCols(..., .make.factors = TRUE)
Arguments
... |
[any] |
.make.factors |
[ |
Value
[CPO
].
CPOTrained State
The created state is empty.
General CPO info
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.
Calling a 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.
See Also
Other CPOs:
cpoApplyFunRegrTarget()
,
cpoApplyFun()
,
cpoAsNumeric()
,
cpoCache()
,
cpoCbind()
,
cpoCollapseFact()
,
cpoDropConstants()
,
cpoDropMostlyConstants()
,
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()
,
cpoMissingIndicators()
,
cpoModelMatrix()
,
cpoOversample()
,
cpoPca()
,
cpoProbEncode()
,
cpoQuantileBinNumerics()
,
cpoRegrResiduals()
,
cpoResponseFromSE()
,
cpoSample()
,
cpoScaleMaxAbs()
,
cpoScaleRange()
,
cpoScale()
,
cpoSelect()
,
cpoSmote()
,
cpoSpatialSign()
,
cpoTransformParams()
,
cpoWrap()
,
makeCPOCase()
,
makeCPOMultiplex()
Examples
res = pid.task %>>% cpoAddCols(gpi = glucose * pressure * insulin, pm = pregnant * mass)
head(getTaskData(res))