Plot a boosted tree model

Read a tree model text dump and plot the model.

xgb.plot.tree(feature_names = NULL, model = NULL, trees = NULL,
  plot_width = NULL, plot_height = NULL, render = TRUE,
  show_node_id = FALSE, ...)

Arguments

feature_names	names of each feature as a character vector.
model	produced by the xgb.train function.
trees	an integer vector of tree indices that should be visualized. If set to NULL, all trees of the model are included. IMPORTANT: the tree index in xgboost model is zero-based (e.g., use trees = 0:2 for the first 3 trees in a model).
plot_width	the width of the diagram in pixels.
plot_height	the height of the diagram in pixels.
render	a logical flag for whether the graph should be rendered (see Value).
show_node_id	a logical flag for whether to show node id's in the graph.
...	currently not used.

Value

When render = TRUE: returns a rendered graph object which is an htmlwidget of class grViz. Similar to ggplot objects, it needs to be printed to see it when not running from command line.

When render = FALSE: silently returns a graph object which is of DiagrammeR's class dgr_graph. This could be useful if one wants to modify some of the graph attributes before rendering the graph with render_graph.

Details

The content of each node is organised that way:

• Feature name.

• Cover: The sum of second order gradient of training data classified to the leaf. If it is square loss, this simply corresponds to the number of instances seen by a split or collected by a leaf during training. The deeper in the tree a node is, the lower this metric will be.

• Gain (for split nodes): the information gain metric of a split (corresponds to the importance of the node in the model).

• Value (for leafs): the margin value that the leaf may contribute to prediction.

The tree root nodes also indicate the Tree index (0-based).

The "Yes" branches are marked by the "< split_value" label. The branches that also used for missing values are marked as bold (as in "carrying extra capacity").

This function uses GraphViz as a backend of DiagrammeR.

Examples

data(agaricus.train, package='xgboost')

bst <- xgboost(data = agaricus.train$data, label = agaricus.train$label, max_depth = 3,
               eta = 1, nthread = 2, nrounds = 2,objective = "binary:logistic")
#> [1]	train-error:0.014433 
#> [2]	train-error:0.001228 
# plot all the trees
xgb.plot.tree(model = bst)
#> Error: DiagrammeR package is required for xgb.plot.tree
# plot only the first tree and display the node ID:
xgb.plot.tree(model = bst, trees = 0, show_node_id = TRUE)
#> Error: DiagrammeR package is required for xgb.plot.tree

if (FALSE) {
# Below is an example of how to save this plot to a file. 
# Note that for `export_graph` to work, the DiagrammeRsvg and rsvg packages must also be installed.
library(DiagrammeR)
gr <- xgb.plot.tree(model=bst, trees=0:1, render=FALSE)
export_graph(gr, 'tree.pdf', width=1500, height=1900)
export_graph(gr, 'tree.png', width=1500, height=1900)
}