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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/removeConstantFeatures.R
\name{removeConstantFeatures}
\alias{removeConstantFeatures}
\title{Remove constant features from a data set.}
\usage{
removeConstantFeatures(
obj,
perc = 0,
dont.rm = character(0L),
na.ignore = FALSE,
wrap.tol = .Machine$double.eps^0.5,
show.info = getMlrOption("show.info"),
...
)
}
\arguments{
\item{obj}{(\link{data.frame} | \link{Task})\cr
Input data.}
\item{perc}{(\code{numeric(1)})\cr
The percentage of a feature values in [0, 1) that must differ from the mode value.
Default is 0, which means only constant features with exactly one observed level are removed.}
\item{dont.rm}{(\link{character})\cr
Names of the columns which must not be deleted.
Default is no columns.}
\item{na.ignore}{(\code{logical(1)})\cr
Should NAs be ignored in the percentage calculation?
(Or should they be treated as a single, extra level in the percentage calculation?)
Note that if the feature has only missing values, it is always removed.
Default is \code{FALSE}.}
\item{wrap.tol}{(\code{numeric(1)})\cr
Numerical tolerance to treat two numbers as equal.
Variables stored as \code{double} will get rounded accordingly before computing the mode.
Default is \code{sqrt(.Maschine$double.eps)}.}
\item{show.info}{(\code{logical(1)})\cr
Print verbose output on console?
Default is set via \link{configureMlr}.}
\item{...}{To ensure backward compatibility with old argument \code{tol}}
}
\value{
\link{data.frame} | \link{Task}. Same type as \code{obj}.
}
\description{
Constant features can lead to errors in some models and obviously provide
no information in the training set that can be learned from.
With the argument \dQuote{perc}, there is a possibility to also remove
features for which less than \dQuote{perc} percent of the observations
differ from the mode value.
}
\seealso{
Other eda_and_preprocess:
\code{\link{capLargeValues}()},
\code{\link{createDummyFeatures}()},
\code{\link{dropFeatures}()},
\code{\link{mergeSmallFactorLevels}()},
\code{\link{normalizeFeatures}()},
\code{\link{summarizeColumns}()},
\code{\link{summarizeLevels}()}
}
\concept{eda_and_preprocess}
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