cpoIca {mlrCPO}

Construct a CPO for ICA Preprocessing

Description

This is a CPOConstructor to be used to create a CPO. It is called like any R function and returns the created CPO.

Use the fastICA function implementing the “FastICA algorithm”. See the documentation there.

Usage

cpoIca(
  n.comp = NULL,
  alg.typ = "parallel",
  fun = "logcosh",
  alpha = 1,
  method = "C",
  maxit = 200,
  tol = 1e-04,
  verbose = FALSE,
  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

n.comp

[numeric(1) | NULL]
Number of components to extract. Default is NULL, which sets it to the number of available numeric columns.

alg.typ

[character(1)]
Algorithm type. One of “parallel” (default) or “deflation”.

fun

[character(1)]
One of “logcosh” (default) or “exp”.

alpha

[numeric(1)]
In range [1, 2], Used for negentropy calculation when fun is “logcosh”. Default is 1.0.

method

[character(1)]
Internal calculation method. “C” (default) or “R”.

maxit

[numeric(1)]
Maximum number of iterations. Default is 200.

tol

[numeric(1)]
Tolerance for convergence, default is 1e-4.

verbose

[logical(1)]
Default is FALSE.

id

[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.

export

[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”.

affect.type

[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.

affect.index

[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).

affect.names

[character]
Feature names of feature columns to affect. The order of names given is respected. Default is character(0).

affect.pattern

[character(1) | NULL]
grep pattern to match feature names by. Default is NULL (no pattern matching)

affect.invert

[logical(1)]
Whether to affect all features not matched by other affect.* parameters.

affect.pattern.ignore.case

[logical(1)]
Ignore case when matching features with affect.pattern; see grep. Default is FALSE.

affect.pattern.perl

[logical(1)]
Use Perl-style regular expressions for affect.pattern; see grep. Default is FALSE.

affect.pattern.fixed

[logical(1)]
Use fixed matching instead of regular expressions for affect.pattern; see grep. Default is FALSE.

Value

[CPO].

CPOTrained State

The state contains a $control slot with the $K, $W and $A slots of the fastICA call, as well as a $center slot indicating the row-wise center of the training data that will be subtracted before rotation.

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 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(), 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()