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XGBRanker documentation: few clarifications (#8356)

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luca-s 2022-10-18 19:54:14 +02:00 committed by GitHub
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python-package/xgboost/sklearn.py
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@ -1795,11 +1795,16 @@ class XGBRFRegressor(XGBRegressor):
.. note::
Query group information is required for ranking tasks by either using the
`group` parameter or `qid` parameter in `fit` method.
`group` parameter or `qid` parameter in `fit` method. This information is
not required in 'predict' method and multiple groups can be predicted on
a single call to `predict`.
Before fitting the model, your data need to be sorted by query group. When fitting
the model, you need to provide an additional array that contains the size of each
When fitting the model with the `group` parameter, your data need to be sorted
by query group first. `group` must be an array that contains the size of each
query group.
When fitting the model with the `qid` parameter, your data does not need
sorting. `qid` must be an array that contains the group of each training
sample.
For example, if your original data look like:
@ -1821,8 +1826,8 @@ class XGBRFRegressor(XGBRegressor):
| 2 | 1 | x_7 |
+-------+-----------+---------------+
then your group array should be ``[3, 4]``. Sometimes using query id (`qid`)
instead of group can be more convenient.
then `fit` method can be called with either `group` array as ``[3, 4]``
or with `qid` as ``[`1, 1, 1, 2, 2, 2, 2]``, that is the qid column.
""",
)
class XGBRanker(XGBModel, XGBRankerMixIn):