X-Git-Url: https://git.auder.net/images/pieces/Cwda/current/git-logo.png?a=blobdiff_plain;f=man%2FAgghooCV.Rd;h=97d4c41eb273adb5e851b78d382e46613ee9da51;hb=3b8affec63125c3816a3d15f0f49776dc14867a2;hp=75ce9dbe11aa1caa345954620166b043d0b13804;hpb=43a6578d444f388d72755e74c7eed74f3af638ec;p=agghoo.git
diff --git a/man/AgghooCV.Rd b/man/AgghooCV.Rd
index 75ce9db..97d4c41 100644
--- a/man/AgghooCV.Rd
+++ b/man/AgghooCV.Rd
@@ -23,7 +23,7 @@ from the list of models (see 'Model' class).
\subsection{Method \code{new()}}{
Create a new AgghooCV object.
\subsection{Usage}{
-\if{html}{\out{
}}\preformatted{AgghooCV$new(data, target, task, gmodel, loss = NULL)}\if{html}{\out{
}}
+\if{html}{\out{}}\preformatted{AgghooCV$new(data, target, task, gmodel, loss)}\if{html}{\out{
}}
}
\subsection{Arguments}{
@@ -33,11 +33,14 @@ Create a new AgghooCV object.
\item{\code{target}}{Vector of targets (generally numeric or factor)}
-\item{\code{task}}{"regression" or "classification"}
+\item{\code{task}}{"regression" or "classification".
+Default: classification if target not numeric.}
-\item{\code{gmodel}}{Generic model returning a predictive function}
+\item{\code{gmodel}}{Generic model returning a predictive function
+Default: tree if mixed data, knn/ppr otherwise.}
-\item{\code{loss}}{Function assessing the error of a prediction}
+\item{\code{loss}}{Function assessing the error of a prediction
+Default: error rate or mean(abs(error)).}
}
\if{html}{\out{}}
}
@@ -48,19 +51,20 @@ Create a new AgghooCV object.
\subsection{Method \code{fit()}}{
Fit an agghoo model.
\subsection{Usage}{
-\if{html}{\out{}}\preformatted{AgghooCV$fit(CV = list(type = "MC", V = 10, test_size = 0.2, shuffle = TRUE))}\if{html}{\out{
}}
+\if{html}{\out{}}\preformatted{AgghooCV$fit(CV = NULL)}\if{html}{\out{
}}
}
\subsection{Arguments}{
\if{html}{\out{}}
\describe{
\item{\code{CV}}{List describing cross-validation to run. Slots: \cr
-- type: 'vfold' or 'MC' for Monte-Carlo (default: MC) \cr
-- V: number of runs (default: 10) \cr
-- test_size: percentage of data in the test dataset, for MC \cr
- (irrelevant for V-fold). Default: 0.2.
-- shuffle: wether or not to shuffle data before V-fold.
- Irrelevant for Monte-Carlo; default: TRUE}
+ - type: 'vfold' or 'MC' for Monte-Carlo (default: MC) \cr
+ - V: number of runs (default: 10) \cr
+ - test_size: percentage of data in the test dataset, for MC
+ (irrelevant for V-fold). Default: 0.2. \cr
+ - shuffle: wether or not to shuffle data before V-fold.
+ Irrelevant for Monte-Carlo; default: TRUE \cr
+Default (if NULL): type="MC", V=10, test_size=0.2}
}
\if{html}{\out{
}}
}