xgb.plot.tree
Plot a boosted tree model
Read a tree model text dump and plot the model.
Usage
xgb.plot.tree(feature_names = NULL, model = NULL, n_first_tree = NULL,
plot_width = NULL, plot_height = NULL, ...)Arguments
- feature_names
names of each feature as a
charactervector. Can be extracted from a sparse matrix (see example). If model dump already contains feature names, this argument should beNULL.- model
generated by the
xgb.trainfunction. Avoid the creation of a dump file.- n_first_tree
limit the plot to the n first trees. If
NULL, all trees of the model are plotted. Performance can be low for huge models.- plot_width
the width of the diagram in pixels.
- plot_height
the height of the diagram in pixels.
- ...
currently not used.
Details
The content of each node is organised that way:
featurevalue;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.
Value
A DiagrammeR of the model.
Examples
# NOT RUN {
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)
# }