| cpoFilterFeatures {mlrCPO} | R Documentation | 
Filter Features by Thresholding Filter Values
Description
This is a CPOConstructor to be used to create a
CPO. It is called like any R function and returns
the created CPO.
First, calls generateFilterValuesData.
Features are then selected via select and val.
Usage
cpoFilterFeatures(
  method = "randomForestSRC.rfsrc",
  fval = NULL,
  perc = NULL,
  abs = NULL,
  threshold = NULL,
  filter.args = list(),
  id,
  export = "export.default",
  affect.type = NULL,
  affect.index = integer(0),
  affect.names = character(0),
  affect.pattern = NULL,
  affect.invert = FALSE,
  affect.pattern.ignore.case = FALSE,
  affect.pattern.perl = FALSE,
  affect.pattern.fixed = FALSE
)
Arguments
method | 
 [  | 
fval | 
 [  | 
perc | 
 [  | 
abs | 
 [  | 
threshold | 
 [  | 
filter.args | 
 [  | 
id | 
 [  | 
export | 
 [  | 
affect.type | 
 [  | 
affect.index | 
 [  | 
affect.names | 
 [  | 
affect.pattern | 
 [  | 
affect.invert | 
 [  | 
affect.pattern.ignore.case | 
 [  | 
affect.pattern.perl | 
 [  | 
affect.pattern.fixed | 
 [  | 
Value
[CPO].
General CPO info
This function creates a CPO object, which can be applied to
Tasks, data.frames, 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 filter: 
cpoFilterAnova(),
cpoFilterCarscore(),
cpoFilterChiSquared(),
cpoFilterGainRatio(),
cpoFilterInformationGain(),
cpoFilterKruskal(),
cpoFilterLinearCorrelation(),
cpoFilterMrmr(),
cpoFilterOneR(),
cpoFilterPermutationImportance(),
cpoFilterRankCorrelation(),
cpoFilterRelief(),
cpoFilterRfCImportance(),
cpoFilterRfImportance(),
cpoFilterRfSRCImportance(),
cpoFilterRfSRCMinDepth(),
cpoFilterSymmetricalUncertainty(),
cpoFilterUnivariate(),
cpoFilterVariance(),
randomForestSRC_filters
Other CPOs: 
cpoApplyFunRegrTarget(),
cpoApplyFun(),
cpoAsNumeric(),
cpoCache(),
cpoCbind(),
cpoCollapseFact(),
cpoDropConstants(),
cpoDropMostlyConstants(),
cpoDummyEncode(),
cpoFilterAnova(),
cpoFilterCarscore(),
cpoFilterChiSquared(),
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 filter: 
cpoFilterAnova(),
cpoFilterCarscore(),
cpoFilterChiSquared(),
cpoFilterGainRatio(),
cpoFilterInformationGain(),
cpoFilterKruskal(),
cpoFilterLinearCorrelation(),
cpoFilterMrmr(),
cpoFilterOneR(),
cpoFilterPermutationImportance(),
cpoFilterRankCorrelation(),
cpoFilterRelief(),
cpoFilterRfCImportance(),
cpoFilterRfImportance(),
cpoFilterRfSRCImportance(),
cpoFilterRfSRCMinDepth(),
cpoFilterSymmetricalUncertainty(),
cpoFilterUnivariate(),
cpoFilterVariance(),
randomForestSRC_filters