projects / agghoo.git / blame
| Commit | Line | Data |
|---|---|---|
| c5946158 BA |
1 | % Generated by roxygen2: do not edit by hand |
| 2 | % Please edit documentation in R/R6_Model.R | |
| 3 | \name{Model} | |
| 4 | \alias{Model} | |
| 5 | \title{R6 class representing a (generic) model.} | |
| 6 | \description{ | |
| 7 | "Model" class, containing a (generic) learning function, which from | |
| 8 | data + target [+ params] returns a prediction function X --> y. | |
| 9 | Parameters for cross-validation are either provided or estimated. | |
| 10 | Model family can be chosen among "rf", "tree", "ppr" and "knn" for now. | |
| 11 | } | |
| 12 | \section{Public fields}{ | |
| 13 | \if{html}{\out{<div class="r6-fields">}} | |
| 14 | \describe{ | |
| 15 | \item{\code{nmodels}}{Number of parameters (= number of [predictive] models)} | |
| 16 | } | |
| 17 | \if{html}{\out{</div>}} | |
| 18 | } | |
| 19 | \section{Methods}{ | |
| 20 | \subsection{Public methods}{ | |
| 21 | \itemize{ | |
| 22 | \item \href{#method-new}{\code{Model$new()}} | |
| 23 | \item \href{#method-get}{\code{Model$get()}} | |
| 24 | \item \href{#method-clone}{\code{Model$clone()}} | |
| 25 | } | |
| 26 | } | |
| 27 | \if{html}{\out{<hr>}} | |
| 28 | \if{html}{\out{<a id="method-new"></a>}} | |
| 29 | \if{latex}{\out{\hypertarget{method-new}{}}} | |
| 30 | \subsection{Method \code{new()}}{ | |
| 31 | Create a new generic model. | |
| 32 | \subsection{Usage}{ | |
| d9a139b5 | 33 | \if{html}{\out{<div class="r">}}\preformatted{Model$new(data, target, task, gmodel = NULL, params = NULL)}\if{html}{\out{</div>}} |
| c5946158 BA |
34 | } |
| 35 | ||
| 36 | \subsection{Arguments}{ | |
| 37 | \if{html}{\out{<div class="arguments">}} | |
| 38 | \describe{ | |
| 39 | \item{\code{data}}{Matrix or data.frame} | |
| 40 | ||
| 41 | \item{\code{target}}{Vector of targets (generally numeric or factor)} | |
| 42 | ||
| 43 | \item{\code{task}}{"regression" or "classification"} | |
| 44 | ||
| 45 | \item{\code{gmodel}}{Generic model returning a predictive function; chosen | |
| 46 | automatically given data and target nature if not provided.} | |
| 47 | ||
| 48 | \item{\code{params}}{List of parameters for cross-validation (each defining a model)} | |
| 49 | } | |
| 50 | \if{html}{\out{</div>}} | |
| 51 | } | |
| 52 | } | |
| 53 | \if{html}{\out{<hr>}} | |
| 54 | \if{html}{\out{<a id="method-get"></a>}} | |
| 55 | \if{latex}{\out{\hypertarget{method-get}{}}} | |
| 56 | \subsection{Method \code{get()}}{ | |
| 57 | Returns the model at index "index", trained on dataHO/targetHO. | |
| 58 | index is between 1 and self$nmodels. | |
| 59 | \subsection{Usage}{ | |
| 60 | \if{html}{\out{<div class="r">}}\preformatted{Model$get(dataHO, targetHO, index)}\if{html}{\out{</div>}} | |
| 61 | } | |
| 62 | ||
| 63 | \subsection{Arguments}{ | |
| 64 | \if{html}{\out{<div class="arguments">}} | |
| 65 | \describe{ | |
| 66 | \item{\code{dataHO}}{Matrix or data.frame} | |
| 67 | ||
| 68 | \item{\code{targetHO}}{Vector of targets (generally numeric or factor)} | |
| 69 | ||
| 70 | \item{\code{index}}{Index of the model in 1...nmodels} | |
| 71 | } | |
| 72 | \if{html}{\out{</div>}} | |
| 73 | } | |
| 74 | } | |
| 75 | \if{html}{\out{<hr>}} | |
| 76 | \if{html}{\out{<a id="method-clone"></a>}} | |
| 77 | \if{latex}{\out{\hypertarget{method-clone}{}}} | |
| 78 | \subsection{Method \code{clone()}}{ | |
| 79 | The objects of this class are cloneable with this method. | |
| 80 | \subsection{Usage}{ | |
| 81 | \if{html}{\out{<div class="r">}}\preformatted{Model$clone(deep = FALSE)}\if{html}{\out{</div>}} | |
| 82 | } | |
| 83 | ||
| 84 | \subsection{Arguments}{ | |
| 85 | \if{html}{\out{<div class="arguments">}} | |
| 86 | \describe{ | |
| 87 | \item{\code{deep}}{Whether to make a deep clone.} | |
| 88 | } | |
| 89 | \if{html}{\out{</div>}} | |
| 90 | } | |
| 91 | } | |
| 92 | } |