[doc] Add missing document for pyspark ranker. [skip ci] (#8692)

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Jiaming Yuan 2023-01-18 07:52:18 +08:00 committed by GitHub
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3 changed files with 16 additions and 5 deletions

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@ -173,3 +173,13 @@ PySpark API
:members: :members:
:inherited-members: :inherited-members:
:show-inheritance: :show-inheritance:
.. autoclass:: xgboost.spark.SparkXGBRanker
:members:
:inherited-members:
:show-inheritance:
.. autoclass:: xgboost.spark.SparkXGBRankerModel
:members:
:inherited-members:
:show-inheritance:

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@ -45,7 +45,7 @@ such as ``weight_col``, ``validation_indicator_col``, ``use_gpu``, for details p
The following code snippet shows how to train a spark xgboost regressor model, The following code snippet shows how to train a spark xgboost regressor model,
first we need to prepare a training dataset as a spark dataframe contains first we need to prepare a training dataset as a spark dataframe contains
"label" column and "features" column(s), the "features" column(s) must be ``pyspark.ml.linalg.Vector` "label" column and "features" column(s), the "features" column(s) must be ``pyspark.ml.linalg.Vector``
type or spark array type or a list of feature column names. type or spark array type or a list of feature column names.
@ -56,7 +56,7 @@ type or spark array type or a list of feature column names.
The following code snippet shows how to predict test data using a spark xgboost regressor model, The following code snippet shows how to predict test data using a spark xgboost regressor model,
first we need to prepare a test dataset as a spark dataframe contains first we need to prepare a test dataset as a spark dataframe contains
"features" and "label" column, the "features" column must be ``pyspark.ml.linalg.Vector` "features" and "label" column, the "features" column must be ``pyspark.ml.linalg.Vector``
type or spark array type. type or spark array type.
.. code-block:: python .. code-block:: python

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@ -1,5 +1,4 @@
"""PySpark XGBoost integration interface """PySpark XGBoost integration interface"""
"""
try: try:
import pyspark import pyspark
@ -10,6 +9,7 @@ from .estimator import (
SparkXGBClassifier, SparkXGBClassifier,
SparkXGBClassifierModel, SparkXGBClassifierModel,
SparkXGBRanker, SparkXGBRanker,
SparkXGBRankerModel,
SparkXGBRegressor, SparkXGBRegressor,
SparkXGBRegressorModel, SparkXGBRegressorModel,
) )
@ -20,4 +20,5 @@ __all__ = [
"SparkXGBRegressor", "SparkXGBRegressor",
"SparkXGBRegressorModel", "SparkXGBRegressorModel",
"SparkXGBRanker", "SparkXGBRanker",
"SparkXGBRankerModel",
] ]