#' from the list of models (see 'Model' class).
#'
#' @export
-Agghoo <- R6::R6Class("Agghoo",
+AgghooCV <- R6::R6Class("AgghooCV",
public = list(
- #' @description Create a new Agghoo object.
+ #' @description Create a new AgghooCV object.
#' @param data Matrix or data.frame
#' @param target Vector of targets (generally numeric or factor)
#' @param task "regression" or "classification"
#' Default: see R6::Model.
#' @param quality A function assessing the quality of a prediction.
#' Arguments are y1 and y2 (comparing a prediction to known values).
-#' Default: see R6::Agghoo.
+#' Default: see R6::AgghooCV.
#'
-#' @return An R6::Agghoo object.
+#' @return An R6::AgghooCV object.
#'
#' @examples
#' # Regression:
}
# Build Model object (= list of parameterized models)
model <- Model$new(data, target, task, gmodel, params)
- # Return Agghoo object, to run and predict
- Agghoo$new(data, target, task, model, quality)
+ # Return AgghooCV object, to run and predict
+ AgghooCV$new(data, target, task, model, quality)
}
#' compareToStandard
% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/R6_Agghoo.R
-\name{Agghoo}
-\alias{Agghoo}
+% Please edit documentation in R/R6_AgghooCV.R
+\name{AgghooCV}
+\alias{AgghooCV}
\title{R6 class with agghoo functions fit() and predict().}
\description{
Class encapsulating the methods to run to obtain the best predictor
\section{Methods}{
\subsection{Public methods}{
\itemize{
-\item \href{#method-new}{\code{Agghoo$new()}}
-\item \href{#method-fit}{\code{Agghoo$fit()}}
-\item \href{#method-predict}{\code{Agghoo$predict()}}
-\item \href{#method-clone}{\code{Agghoo$clone()}}
+\item \href{#method-new}{\code{AgghooCV$new()}}
+\item \href{#method-fit}{\code{AgghooCV$fit()}}
+\item \href{#method-predict}{\code{AgghooCV$predict()}}
+\item \href{#method-clone}{\code{AgghooCV$clone()}}
}
}
\if{html}{\out{<hr>}}
\if{html}{\out{<a id="method-new"></a>}}
\if{latex}{\out{\hypertarget{method-new}{}}}
\subsection{Method \code{new()}}{
-Create a new Agghoo object.
+Create a new AgghooCV object.
\subsection{Usage}{
-\if{html}{\out{<div class="r">}}\preformatted{Agghoo$new(data, target, task, gmodel, quality = NA)}\if{html}{\out{</div>}}
+\if{html}{\out{<div class="r">}}\preformatted{AgghooCV$new(data, target, task, gmodel, quality = NA)}\if{html}{\out{</div>}}
}
\subsection{Arguments}{
\subsection{Method \code{fit()}}{
Fit an agghoo model.
\subsection{Usage}{
-\if{html}{\out{<div class="r">}}\preformatted{Agghoo$fit(
+\if{html}{\out{<div class="r">}}\preformatted{AgghooCV$fit(
CV = list(type = "MC", V = 10, test_size = 0.2, shuffle = TRUE),
mode = "agghoo"
)}\if{html}{\out{</div>}}
\subsection{Method \code{predict()}}{
Predict an agghoo model (after calling fit())
\subsection{Usage}{
-\if{html}{\out{<div class="r">}}\preformatted{Agghoo$predict(X, weight = "uniform")}\if{html}{\out{</div>}}
+\if{html}{\out{<div class="r">}}\preformatted{AgghooCV$predict(X, weight = "uniform")}\if{html}{\out{</div>}}
}
\subsection{Arguments}{
\subsection{Method \code{clone()}}{
The objects of this class are cloneable with this method.
\subsection{Usage}{
-\if{html}{\out{<div class="r">}}\preformatted{Agghoo$clone(deep = FALSE)}\if{html}{\out{</div>}}
+\if{html}{\out{<div class="r">}}\preformatted{AgghooCV$clone(deep = FALSE)}\if{html}{\out{</div>}}
}
\subsection{Arguments}{