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[R] Implement feature weights. (#7660)

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Jiaming Yuan
2022-02-16 22:20:52 +08:00
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parent 0149f81a5a
commit 12949c6b31
3 changed files with 37 additions and 4 deletions
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doc/parameter.rst
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@@ -115,10 +115,9 @@ Parameters for Tree Booster
'colsample_bynode':0.5}`` with 64 features will leave 8 features to choose from at
each split.
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.
Using the Python or the R package, 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``]