Visualization of the ensemble of trees as a single collective unit.
xgb.plot.multi.trees(model, feature_names = NULL, features_keep = 5, plot_width = NULL, plot_height = NULL, render = TRUE, ...)
model | produced by the |
---|---|
feature_names | names of each feature as a |
features_keep | number of features to keep in each position of the multi trees. |
plot_width | width in pixels of the graph to produce |
plot_height | height in pixels of the graph to produce |
render | a logical flag for whether the graph should be rendered (see Value). |
... | currently not used |
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
.
This function tries to capture the complexity of a gradient boosted tree model in a cohesive way by compressing an ensemble of trees into a single tree-graph representation. The goal is to improve the interpretability of a model generally seen as black box.
Note: this function is applicable to tree booster-based models only.
It takes advantage of the fact that the shape of a binary tree is only defined by its depth (therefore, in a boosting model, all trees have similar shape).
Moreover, the trees tend to reuse the same features.
The function projects each tree onto one, and keeps for each position the
features_keep
first features (based on the Gain per feature measure).
This function is inspired by this blog post: https://wellecks.wordpress.com/2015/02/21/peering-into-the-black-box-visualizing-lambdamart/
data(agaricus.train, package='xgboost') bst <- xgboost(data = agaricus.train$data, label = agaricus.train$label, max_depth = 15, eta = 1, nthread = 2, nrounds = 30, objective = "binary:logistic", min_child_weight = 50, verbose = 0) p <- xgb.plot.multi.trees(model = bst, features_keep = 3)#>#> Error in loadNamespace(name): there is no package called ‘DiagrammeR’print(p)#> Error in print(p): object 'p' not foundif (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.multi.trees(model=bst, features_keep = 3, render=FALSE) export_graph(gr, 'tree.pdf', width=1500, height=600) }