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Specify shape in prediction contrib and interaction. (#6614)

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This commit is contained in:
Jiaming Yuan
2021-01-26 02:08:22 +08:00
committed by GitHub
parent 8942c98054
commit 4bf23c2391
4 changed files with 155 additions and 87 deletions
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doc/tutorials/dask.rst
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@@ -95,14 +95,21 @@ For prediction, pass the ``output`` returned by ``train`` into ``xgb.dask.predic
.. code-block:: python
prediction = xgb.dask.predict(client, output, dtrain)
# Or equivalently, pass ``output['booster']``:
prediction = xgb.dask.predict(client, output['booster'], dtrain)
Or equivalently, pass ``output['booster']``:
Eliminating the construction of DaskDMatrix is also possible, this can make the
computation a bit faster when meta information like ``base_margin`` is not needed:
.. code-block:: python
prediction = xgb.dask.predict(client, output['booster'], dtrain)
prediction = xgb.dask.predict(client, output, X)
# Use inplace version.
prediction = xgb.dask.inplace_predict(client, output, X)
Here ``prediction`` is a dask ``Array`` object containing predictions from model.
Here ``prediction`` is a dask ``Array`` object containing predictions from model if input
is a ``DaskDMatrix`` or ``da.Array``. For ``dd.DataFrame``, the return value is a
``dd.Series``.
Alternatively, XGBoost also implements the Scikit-Learn interface with ``DaskXGBClassifier``
and ``DaskXGBRegressor``. See ``xgboost/demo/dask`` for more examples.