python xgboost建模过程_如何在python / R中访问xgboost模型的单个树

ゞ浴缸里的玫瑰 2023-01-09 14:23 105阅读 0赞

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How to get access of individual trees of a xgboost model in python/R ?

Below I'm getting from Random Forest trees from sklearn.

estimator = RandomForestRegressor(oob\_score=True, n\_estimators=10,max\_features='auto') estimator.fit(tarning\_data,traning\_target) tree1 = estimator.estimators\_\[0\]

leftChild = tree1.tree\_.children\_left

rightChild = tree1.tree\_.children\_right

解决方案

Do you want to inspect the trees?

In Python, you can dump the trees as a list of strings:

m = xgb.XGBClassifier(max\_depth=2, n\_estimators=3).fit(X, y)

m.get\_booster().get\_dump()

\['0:\[sincelastrun<23.2917\] yes=1,no=2,missing=2\\n\\t1:\[sincelastrun<18.0417\] yes=3,no=4,missing=4\\n\\t\\t3:leaf=-0.0965415\\n\\t\\t4:leaf=-0.0679503\\n\\t2:\[sincelastrun<695.025\] yes=5,no=6,missing=6\\n\\t\\t5:leaf=-0.0992546\\n\\t\\t6:leaf=-0.0984374\\n',

'0:\[sincelastrun<23.2917\] yes=1,no=2,missing=2\\n\\t1:\[sincelastrun<16.8917\] yes=3,no=4,missing=4\\n\\t\\t3:leaf=-0.0928132\\n\\t\\t4:leaf=-0.0676056\\n\\t2:\[sincelastrun<695.025\] yes=5,no=6,missing=6\\n\\t\\t5:leaf=-0.0945284\\n\\t\\t6:leaf=-0.0937463\\n',

'0:\[sincelastrun<23.2917\] yes=1,no=2,missing=2\\n\\t1:\[sincelastrun<18.175\] yes=3,no=4,missing=4\\n\\t\\t3:leaf=-0.0878571\\n\\t\\t4:leaf=-0.0610089\\n\\t2:\[sincelastrun<695.025\] yes=5,no=6,missing=6\\n\\t\\t5:leaf=-0.0904395\\n\\t\\t6:leaf=-0.0896808\\n'\]

Or dump them to a file (with nice formatting):

m.get\_booster().dump\_model("out.txt")

booster\[0\]:

0:\[sincelastrun<23.2917\] yes=1,no=2,missing=2

1:\[sincelastrun<18.0417\] yes=3,no=4,missing=4

3:leaf=-0.0965415

4:leaf=-0.0679503

2:\[sincelastrun<695.025\] yes=5,no=6,missing=6

5:leaf=-0.0992546

6:leaf=-0.0984374

booster\[1\]:

0:\[sincelastrun<23.2917\] yes=1,no=2,missing=2