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Document tree method for feature weights. (#6312)

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Jiaming Yuan
2020-10-29 04:42:13 +08:00
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parent 143b278267
commit e8884c4637
2 changed files with 12 additions and 9 deletions
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doc/parameter.rst
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@@ -108,9 +108,10 @@ Parameters for Tree Booster
'colsample_bynode':0.5}`` with 64 features will leave 8 features to choose from at
each split.
On Python interface, one can set the ``feature_weights`` for DMatrix to define the
probability of each feature being selected when using column sampling. There's a
similar parameter for ``fit`` method in sklearn interface.
On Python interface, when using ``hist``, ``gpu_hist`` or ``exact`` tree method, one
can set the ``feature_weights`` for DMatrix to define the probability of each feature
being selected when using column sampling. There's a similar parameter for ``fit``
method in sklearn interface.
* ``lambda`` [default=1, alias: ``reg_lambda``]