This is a CPOConstructor to be used to create a
CPO. It is called like any R function and returns
the created CPO.
Impact coding converts factor levels of each (factorial) column to the difference between each target level's conditional log-likelihood given this level, and the target level's global log-likelihood.
cpoImpactEncodeClassif(smoothing = 1e-04, 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)[numeric(1)]
A finite positive value used for smoothing. Mostly relevant if
a factor does not coincide with a target factor level (and
would otherwise give an infinite logit value).
Default is 1e-4.
[character(1)]
id to use as prefix for the CPO's hyperparameters. this
must be used to avoid name clashes when composing two
CPOs of the same type, or with learners or other CPOS
with hyperparameters with clashing names.
[character]
Either a character vector indicating the parameters to
export as hyperparameters, or one of the special values
“export.all” (export all parameters),
“export.default” (export all parameters that are exported by default),
“export.set” (export all parameters that were set during construction),
“export.default.set” (export the intersection of the “default” and “set” parameters),
“export.unset” (export all parameters that were not set during construction) or
“export.default.unset” (export the intersection of the “default” and “unset” parameters).
Default is “export.default”.
[character | NULL]
Type of columns to affect. A subset of “numeric”, “factor”, “ordered”, “other”, or NULL
to not match by column type. Default is NULL.
[numeric]
Indices of feature columns to affect. The order of indices given is respected. Target column indices are not counted
(since target columns are always included). Default is integer(0).
[character]
Feature names of feature columns to affect. The order of names given is respected. Default is character(0).
[character(1) | NULL]
grep pattern to match feature names by. Default is NULL (no pattern matching)
[logical(1)]
Whether to affect all features not matched by other affect.* parameters.
[logical(1)]
Ignore case when matching features with affect.pattern; see grep. Default is FALSE.
[logical(1)]
Use Perl-style regular expressions for affect.pattern; see grep. Default is FALSE.
[logical(1)]
Use fixed matching instead of regular expressions for affect.pattern; see grep. Default is FALSE.
[CPO].
The state's $control slot is a list of matrices for each
factorial data column. Each of these matrices has rows for each of
the data column's levels, and columns for each
of the target factor levels, and gives the respective impact values.
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.
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, cpoCbind,
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,
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