"Model" class, containing a (generic) learning function, which from
data + target [+ params] returns a prediction function X --> y.
Parameters for cross-validation are either provided or estimated.
-Model family can be chosen among "rf", "tree", "ppr" and "knn" for now.
+Model family can be chosen among "tree", "ppr" and "knn" for now.
}
\section{Public fields}{
\if{html}{\out{<div class="r6-fields">}}
\itemize{
\item \href{#method-new}{\code{Model$new()}}
\item \href{#method-get}{\code{Model$get()}}
+\item \href{#method-getParam}{\code{Model$getParam()}}
\item \href{#method-clone}{\code{Model$clone()}}
}
}
\if{latex}{\out{\hypertarget{method-get}{}}}
\subsection{Method \code{get()}}{
Returns the model at index "index", trained on dataHO/targetHO.
-index is between 1 and self$nmodels.
\subsection{Usage}{
\if{html}{\out{<div class="r">}}\preformatted{Model$get(dataHO, targetHO, index)}\if{html}{\out{</div>}}
}
\item{\code{targetHO}}{Vector of targets (generally numeric or factor)}
+\item{\code{index}}{Index of the model in 1...nmodels}
+}
+\if{html}{\out{</div>}}
+}
+}
+\if{html}{\out{<hr>}}
+\if{html}{\out{<a id="method-getParam"></a>}}
+\if{latex}{\out{\hypertarget{method-getParam}{}}}
+\subsection{Method \code{getParam()}}{
+Returns the parameter at index "index".
+\subsection{Usage}{
+\if{html}{\out{<div class="r">}}\preformatted{Model$getParam(index)}\if{html}{\out{</div>}}
+}
+
+\subsection{Arguments}{
+\if{html}{\out{<div class="arguments">}}
+\describe{
\item{\code{index}}{Index of the model in 1...nmodels}
}
\if{html}{\out{</div>}}