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add new parameters model to avoid the use of dump file for functions plot, dt.tree, importance

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add new size parameter for plot function
This commit is contained in:
El Potaeto
2015-01-11 09:40:55 +01:00
parent c8c5789efd
commit 31a3b38ef8
5 changed files with 40 additions and 25 deletions
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10
R-package/man/xgb.model.dt.tree.Rd
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@@ -4,14 +4,18 @@
\alias{xgb.model.dt.tree}
\title{Convert tree model dump to data.table}
\usage{
xgb.model.dt.tree(feature_names = NULL, filename_dump = NULL, text = NULL,
n_first_tree = NULL)
xgb.model.dt.tree(feature_names = NULL, filename_dump = NULL,
model = NULL, text = NULL, n_first_tree = NULL)
}
\arguments{
\item{feature_names}{names of each feature as a character vector. Can be extracted from a sparse matrix (see example). If model dump already contains feature names, this argument should be \code{NULL}.}
\item{filename_dump}{the path to the text file storing the model. Model dump must include the gain per feature and per tree (parameter \code{with.stats = T} in function \code{xgb.dump}).}
\item{model}{dump generated by the \code{xgb.train} function. Avoid the creation of a dump file.}
\item{text}{dump generated by the \code{xgb.dump} function. Avoid the creation of a dump file. Model dump must include the gain per feature and per tree (parameter \code{with.stats = T} in function \code{xgb.dump}).}
\item{n_first_tree}{limit the plot to the n first trees. If \code{NULL}, all trees of the model are plotted. Performance can be low for huge models.}
}
\value{
@@ -49,6 +53,6 @@ bst <- xgboost(data = train$data, label = train$label, max.depth = 2,
xgb.dump(bst, 'xgb.model.dump', with.stats = T)
#agaricus.test$data@Dimnames[[2]] represents the column names of the sparse matrix.
xgb.model.dt.tree(agaricus.train$data@Dimnames[[2]], 'xgb.model.dump')
xgb.model.dt.tree(agaricus.train$data@Dimnames[[2]], filename_dump = 'xgb.model.dump')
}

4
R-package/man/xgb.plot.tree.Rd
View File

@@ -5,7 +5,7 @@
\title{Plot a boosted tree model}
\usage{
xgb.plot.tree(feature_names = NULL, filename_dump = NULL, model = NULL,
n_first_tree = NULL, styles = NULL)
n_first_tree = NULL, CSSstyle = NULL)
}
\arguments{
\item{feature_names}{names of each feature as a character vector. Can be extracted from a sparse matrix (see example). If model dump already contains feature names, this argument should be \code{NULL}.}
@@ -16,7 +16,7 @@ xgb.plot.tree(feature_names = NULL, filename_dump = NULL, model = NULL,
\item{n_first_tree}{limit the plot to the n first trees. If \code{NULL}, all trees of the model are plotted. Performance can be low for huge models.}
\item{style}{a \code{character} vector storing a css style to customize the appearance of nodes. Look at the \href{https://github.com/knsv/mermaid/wiki}{Mermaid wiki} for more information.}
\item{CSSstyle}{a \code{character} vector storing a css style to customize the appearance of nodes. Look at the \href{https://github.com/knsv/mermaid/wiki}{Mermaid wiki} for more information.}
}
\value{
A \code{DiagrammeR} of the model.