% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/PipeOpTrafo.R
\name{mlr_pipeops_targettrafoscalerange}
\alias{mlr_pipeops_targettrafoscalerange}
\alias{PipeOpTargetTrafoScaleRange}
\title{Linearly Transform a Numeric Target to Match Given Boundaries}
\format{
\code{\link[R6:R6Class]{R6Class}} object inheriting from \code{\link{PipeOpTargetTrafo}}/\code{\link{PipeOp}}
}
\description{
Linearly transforms a numeric target of a \code{\link[mlr3:TaskRegr]{TaskRegr}} so it is between \code{lower}
and \code{upper}. The formula for this is \eqn{x' = offset + x * scale},
where \eqn{scale} is \eqn{(upper - lower) / (max(x) - min(x))} and
\eqn{offset} is \eqn{-min(x) * scale + lower}. The same transformation is applied during training and
prediction.
}
\section{Construction}{


\if{html}{\out{<div class="sourceCode">}}\preformatted{PipeOpTargetTrafoScaleRange$new(id = "targettrafoscalerange", param_vals = list())
}\if{html}{\out{</div>}}
\itemize{
\item \code{id} :: \code{character(1)}\cr
Identifier of resulting object, default \code{"targettrafoscalerange"}.
\item \code{param_vals} :: named \code{list}\cr
List of hyperparameter settings, overwriting the hyperparameter settings that would otherwise
be set during construction. Default \code{list()}.
}
}

\section{Input and Output Channels}{

Input and output channels are inherited from \code{\link{PipeOpTargetTrafo}}.
}

\section{State}{

The \verb{$state} is a named \code{list} containing the slots \verb{$offset} and \verb{$scale}.
}

\section{Parameters}{

The parameters are the parameters inherited from \code{\link{PipeOpTargetTrafo}}, as well as:
\itemize{
\item \code{lower} :: \code{numeric(1)}\cr
Target value of smallest item of input target. Initialized to 0.
\item \code{upper} :: \code{numeric(1)}\cr
Target value of greatest item of input target. Initialized to 1.
}
}

\section{Internals}{

Overloads \code{\link{PipeOpTargetTrafo}}'s \code{.get_state()}, \code{.transform()}, and
\code{.invert()}. Should be used in combination with \code{\link{PipeOpTargetInvert}}.
}

\section{Methods}{

Only methods inherited from \code{\link{PipeOpTargetTrafo}}/\code{\link{PipeOp}}.
}

\examples{
\dontshow{if (requireNamespace("rpart")) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
library(mlr3)
task = tsk("boston_housing")
po = PipeOpTargetTrafoScaleRange$new()

po$train(list(task))
po$predict(list(task))

#syntactic sugar for a graph using ppl():
ttscalerange = ppl("targettrafo", trafo_pipeop = PipeOpTargetTrafoScaleRange$new(),
  graph = PipeOpLearner$new(LearnerRegrRpart$new()))
ttscalerange$train(task)
ttscalerange$predict(task)
ttscalerange$state$regr.rpart
\dontshow{\}) # examplesIf}
}
\seealso{
https://mlr-org.com/pipeops.html

Other PipeOps: 
\code{\link{PipeOp}},
\code{\link{PipeOpEnsemble}},
\code{\link{PipeOpImpute}},
\code{\link{PipeOpTargetTrafo}},
\code{\link{PipeOpTaskPreproc}},
\code{\link{PipeOpTaskPreprocSimple}},
\code{\link{mlr_pipeops}},
\code{\link{mlr_pipeops_adas}},
\code{\link{mlr_pipeops_blsmote}},
\code{\link{mlr_pipeops_boxcox}},
\code{\link{mlr_pipeops_branch}},
\code{\link{mlr_pipeops_chunk}},
\code{\link{mlr_pipeops_classbalancing}},
\code{\link{mlr_pipeops_classifavg}},
\code{\link{mlr_pipeops_classweights}},
\code{\link{mlr_pipeops_colapply}},
\code{\link{mlr_pipeops_collapsefactors}},
\code{\link{mlr_pipeops_colroles}},
\code{\link{mlr_pipeops_copy}},
\code{\link{mlr_pipeops_datefeatures}},
\code{\link{mlr_pipeops_encode}},
\code{\link{mlr_pipeops_encodeimpact}},
\code{\link{mlr_pipeops_encodelmer}},
\code{\link{mlr_pipeops_featureunion}},
\code{\link{mlr_pipeops_filter}},
\code{\link{mlr_pipeops_fixfactors}},
\code{\link{mlr_pipeops_histbin}},
\code{\link{mlr_pipeops_ica}},
\code{\link{mlr_pipeops_imputeconstant}},
\code{\link{mlr_pipeops_imputehist}},
\code{\link{mlr_pipeops_imputelearner}},
\code{\link{mlr_pipeops_imputemean}},
\code{\link{mlr_pipeops_imputemedian}},
\code{\link{mlr_pipeops_imputemode}},
\code{\link{mlr_pipeops_imputeoor}},
\code{\link{mlr_pipeops_imputesample}},
\code{\link{mlr_pipeops_kernelpca}},
\code{\link{mlr_pipeops_learner}},
\code{\link{mlr_pipeops_missind}},
\code{\link{mlr_pipeops_modelmatrix}},
\code{\link{mlr_pipeops_multiplicityexply}},
\code{\link{mlr_pipeops_multiplicityimply}},
\code{\link{mlr_pipeops_mutate}},
\code{\link{mlr_pipeops_nearmiss}},
\code{\link{mlr_pipeops_nmf}},
\code{\link{mlr_pipeops_nop}},
\code{\link{mlr_pipeops_ovrsplit}},
\code{\link{mlr_pipeops_ovrunite}},
\code{\link{mlr_pipeops_pca}},
\code{\link{mlr_pipeops_proxy}},
\code{\link{mlr_pipeops_quantilebin}},
\code{\link{mlr_pipeops_randomprojection}},
\code{\link{mlr_pipeops_randomresponse}},
\code{\link{mlr_pipeops_regravg}},
\code{\link{mlr_pipeops_removeconstants}},
\code{\link{mlr_pipeops_renamecolumns}},
\code{\link{mlr_pipeops_replicate}},
\code{\link{mlr_pipeops_rowapply}},
\code{\link{mlr_pipeops_scale}},
\code{\link{mlr_pipeops_scalemaxabs}},
\code{\link{mlr_pipeops_scalerange}},
\code{\link{mlr_pipeops_select}},
\code{\link{mlr_pipeops_smote}},
\code{\link{mlr_pipeops_smotenc}},
\code{\link{mlr_pipeops_spatialsign}},
\code{\link{mlr_pipeops_subsample}},
\code{\link{mlr_pipeops_targetinvert}},
\code{\link{mlr_pipeops_targetmutate}},
\code{\link{mlr_pipeops_textvectorizer}},
\code{\link{mlr_pipeops_threshold}},
\code{\link{mlr_pipeops_tomek}},
\code{\link{mlr_pipeops_tunethreshold}},
\code{\link{mlr_pipeops_unbranch}},
\code{\link{mlr_pipeops_updatetarget}},
\code{\link{mlr_pipeops_vtreat}},
\code{\link{mlr_pipeops_yeojohnson}}
}
\concept{PipeOps}
