5a2dcd1c33
* [R] Provide better guidance for persisting XGBoost model * Update saving_model.rst * Add a paragraph about xgb.serialize()
92 lines
3.2 KiB
R
92 lines
3.2 KiB
R
% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/xgb.plot.tree.R
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\name{xgb.plot.tree}
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\alias{xgb.plot.tree}
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\title{Plot a boosted tree model}
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\usage{
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xgb.plot.tree(
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feature_names = NULL,
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model = NULL,
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trees = NULL,
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plot_width = NULL,
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plot_height = NULL,
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render = TRUE,
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show_node_id = FALSE,
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...
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)
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}
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\arguments{
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\item{feature_names}{names of each feature as a \code{character} vector.}
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\item{model}{produced by the \code{xgb.train} function.}
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\item{trees}{an integer vector of tree indices that should be visualized.
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If set to \code{NULL}, all trees of the model are included.
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IMPORTANT: the tree index in xgboost model is zero-based
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(e.g., use \code{trees = 0:2} for the first 3 trees in a model).}
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\item{plot_width}{the width of the diagram in pixels.}
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\item{plot_height}{the height of the diagram in pixels.}
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\item{render}{a logical flag for whether the graph should be rendered (see Value).}
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\item{show_node_id}{a logical flag for whether to show node id's in the graph.}
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\item{...}{currently not used.}
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}
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\value{
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When \code{render = TRUE}:
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returns a rendered graph object which is an \code{htmlwidget} of class \code{grViz}.
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Similar to ggplot objects, it needs to be printed to see it when not running from command line.
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When \code{render = FALSE}:
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silently returns a graph object which is of DiagrammeR's class \code{dgr_graph}.
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This could be useful if one wants to modify some of the graph attributes
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before rendering the graph with \code{\link[DiagrammeR]{render_graph}}.
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}
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\description{
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Read a tree model text dump and plot the model.
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}
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\details{
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The content of each node is organised that way:
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\itemize{
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\item Feature name.
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\item \code{Cover}: The sum of second order gradient of training data classified to the leaf.
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If it is square loss, this simply corresponds to the number of instances seen by a split
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or collected by a leaf during training.
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The deeper in the tree a node is, the lower this metric will be.
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\item \code{Gain} (for split nodes): the information gain metric of a split
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(corresponds to the importance of the node in the model).
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\item \code{Value} (for leafs): the margin value that the leaf may contribute to prediction.
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}
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The tree root nodes also indicate the Tree index (0-based).
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The "Yes" branches are marked by the "< split_value" label.
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The branches that also used for missing values are marked as bold
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(as in "carrying extra capacity").
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This function uses \href{http://www.graphviz.org/}{GraphViz} as a backend of DiagrammeR.
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}
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\examples{
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data(agaricus.train, package='xgboost')
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bst <- xgboost(data = agaricus.train$data, label = agaricus.train$label, max_depth = 3,
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eta = 1, nthread = 2, nrounds = 2,objective = "binary:logistic")
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# plot all the trees
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xgb.plot.tree(model = bst)
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# plot only the first tree and display the node ID:
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xgb.plot.tree(model = bst, trees = 0, show_node_id = TRUE)
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\dontrun{
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# Below is an example of how to save this plot to a file.
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# Note that for `export_graph` to work, the DiagrammeRsvg and rsvg packages must also be installed.
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library(DiagrammeR)
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gr <- xgb.plot.tree(model=bst, trees=0:1, render=FALSE)
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export_graph(gr, 'tree.pdf', width=1500, height=1900)
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export_graph(gr, 'tree.png', width=1500, height=1900)
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}
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}
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