% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/RemoveConstantFeaturesWrapper.R
\name{makeRemoveConstantFeaturesWrapper}
\alias{makeRemoveConstantFeaturesWrapper}
\title{Fuse learner with removal of constant features preprocessing.}
\usage{
makeRemoveConstantFeaturesWrapper(learner, perc = 0,
  dont.rm = character(0L), na.ignore = FALSE,
  tol = .Machine$double.eps^0.5)
}
\arguments{
\item{learner}{[\code{\link{Learner}} | \code{character(1)}]\cr
The learner.
If you pass a string the learner will be created via \code{\link{makeLearner}}.}

\item{perc}{[\code{numeric(1)}]\cr
The percentage of a feature values in [0, 1) that must differ from the mode value.
Default is 0, which means only constant features with exactly one observed level are removed.}

\item{dont.rm}{[\code{character}]\cr
Names of the columns which must not be deleted.
Default is no columns.}

\item{na.ignore}{[\code{logical(1)}]\cr
Should NAs be ignored in the percentage calculation?
(Or should they be treated as a single, extra level in the percentage calculation?)
Note that if the feature has only missing values, it is always removed.
Default is \code{FALSE}.}

\item{tol}{[\code{numeric(1)}]\cr
Numerical tolerance to treat two numbers as equal.
Variables stored as \code{double} will get rounded accordingly before computing the mode.
Default is \code{sqrt(.Maschine$double.eps)}.}
}
\value{
[\code{\link{Learner}}].
}
\description{
Fuses a base learner with the preprocessing implemented in \code{\link{removeConstantFeatures}}.
}
\seealso{
Other wrapper: \code{\link{makeBaggingWrapper}},
  \code{\link{makeConstantClassWrapper}},
  \code{\link{makeCostSensClassifWrapper}},
  \code{\link{makeCostSensRegrWrapper}},
  \code{\link{makeDownsampleWrapper}},
  \code{\link{makeFeatSelWrapper}},
  \code{\link{makeFilterWrapper}},
  \code{\link{makeImputeWrapper}},
  \code{\link{makeMulticlassWrapper}},
  \code{\link{makeMultilabelBinaryRelevanceWrapper}},
  \code{\link{makeMultilabelClassifierChainsWrapper}},
  \code{\link{makeMultilabelDBRWrapper}},
  \code{\link{makeMultilabelNestedStackingWrapper}},
  \code{\link{makeMultilabelStackingWrapper}},
  \code{\link{makeOverBaggingWrapper}},
  \code{\link{makePreprocWrapperCaret}},
  \code{\link{makePreprocWrapper}},
  \code{\link{makeSMOTEWrapper}},
  \code{\link{makeTuneWrapper}},
  \code{\link{makeUndersampleWrapper}},
  \code{\link{makeWeightedClassesWrapper}}
}
