Parse a boosted tree model text dump
Parse a boosted tree model text dump into a data.table structure.
xgb.model.dt.tree( feature_names = NULL, model = NULL, text = NULL, trees = NULL, use_int_id = FALSE, ... )
feature_names |
character vector of feature names. If the model already
contains feature names, those would be used when |
model |
object of class |
text |
|
trees |
an integer vector of tree indices that should be parsed.
If set to |
use_int_id |
a logical flag indicating whether nodes in columns "Yes", "No", "Missing" should be represented as integers (when FALSE) or as "Tree-Node" character strings (when FALSE). |
... |
currently not used. |
A data.table with detailed information about model trees' nodes.
The columns of the data.table are:
Tree: integer ID of a tree in a model (zero-based index)
Node: integer ID of a node in a tree (zero-based index)
ID: character identifier of a node in a model (only when use_int_id=FALSE)
Feature: for a branch node, it's a feature id or name (when available);
for a leaf note, it simply labels it as 'Leaf'
Split: location of the split for a branch node (split condition is always "less than")
Yes: ID of the next node when the split condition is met
No: ID of the next node when the split condition is not met
Missing: ID of the next node when branch value is missing
Quality: either the split gain (change in loss) or the leaf value
Cover: metric related to the number of observation either seen by a split
or collected by a leaf during training.
When use_int_id=FALSE, columns "Yes", "No", and "Missing" point to model-wide node identifiers
in the "ID" column. When use_int_id=TRUE, those columns point to node identifiers from
the corresponding trees in the "Node" column.
# Basic use:
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")
(dt <- xgb.model.dt.tree(colnames(agaricus.train$data), bst))
# This bst model already has feature_names stored with it, so those would be used when
# feature_names is not set:
(dt <- xgb.model.dt.tree(model = bst))
# How to match feature names of splits that are following a current 'Yes' branch:
merge(dt, dt[, .(ID, Y.Feature=Feature)], by.x='Yes', by.y='ID', all.x=TRUE)[order(Tree,Node)]Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.