xgb.plot.tree {xgboost} | R Documentation |
Read a tree model text dump and plot the model.
xgb.plot.tree(feature_names = NULL, model = NULL, n_first_tree = NULL, plot_width = NULL, plot_height = NULL, ...)
feature_names |
names of each feature as a |
model |
generated by the |
n_first_tree |
limit the plot to the n first trees. If |
plot_width |
the width of the diagram in pixels. |
plot_height |
the height of the diagram in pixels. |
... |
currently not used. |
The content of each node is organised that way:
feature
value;
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 in that branch. Deeper in the tree a node is, lower this metric will be;
gain
: metric the importance of the node in the model.
The function uses GraphViz library for that purpose.
A DiagrammeR
of the model.
data(agaricus.train, package='xgboost') bst <- xgboost(data = agaricus.train$data, label = agaricus.train$label, max_depth = 2, eta = 1, nthread = 2, nrounds = 2,objective = "binary:logistic") xgb.plot.tree(feature_names = colnames(agaricus.train$data), model = bst)