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[PySpark] fix raw_prediction_col parameter and minor cleanup #8067

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merged 2 commits into from Jul 16, 2022
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[PySpark] fix raw_prediction_col parameter and minor cleanup #8067

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ecd9ba5
[PySpark] fix raw_prediction_col parameter and minor cleanup
wbo4958 Jul 13, 2022
97b0f17
Merge remote-tracking branch 'upstream/master' into minor-cleanup
wbo4958 Jul 15, 2022
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2 changes: 1 addition & 1 deletion python-package/xgboost/spark/core.py
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Expand Up @@ -88,7 +88,7 @@
"features_col": "featuresCol",
"label_col": "labelCol",
"weight_col": "weightCol",
"raw_prediction_ol": "rawPredictionCol",
"raw_prediction_col": "rawPredictionCol",
"prediction_col": "predictionCol",
"probability_col": "probabilityCol",
"validation_indicator_col": "validationIndicatorCol",
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20 changes: 10 additions & 10 deletions python-package/xgboost/spark/estimator.py
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Expand Up @@ -33,15 +33,15 @@ class SparkXGBRegressor(_SparkXGBEstimator):
callbacks:
The export and import of the callback functions are at best effort.
For details, see :py:attr:`xgboost.spark.SparkXGBRegressor.callbacks` param doc.
validationIndicatorCol
validation_indicator_col
For params related to `xgboost.XGBRegressor` training
with evaluation dataset's supervision, set
:py:attr:`xgboost.spark.SparkXGBRegressor.validationIndicatorCol`
:py:attr:`xgboost.spark.SparkXGBRegressor.validation_indicator_col`
parameter instead of setting the `eval_set` parameter in `xgboost.XGBRegressor`
fit method.
weightCol:
weight_col:
To specify the weight of the training and validation dataset, set
:py:attr:`xgboost.spark.SparkXGBRegressor.weightCol` parameter instead of setting
:py:attr:`xgboost.spark.SparkXGBRegressor.weight_col` parameter instead of setting
`sample_weight` and `sample_weight_eval_set` parameter in `xgboost.XGBRegressor`
fit method.
xgb_model:
Expand Down Expand Up @@ -121,7 +121,7 @@ class SparkXGBClassifier(_SparkXGBEstimator, HasProbabilityCol, HasRawPrediction
another param called `base_margin_col`. see doc below for more details.

SparkXGBClassifier doesn't support setting `output_margin`, but we can get output margin
from the raw prediction column. See `rawPredictionCol` param doc below for more details.
from the raw prediction column. See `raw_prediction_col` param doc below for more details.

SparkXGBClassifier doesn't support `validate_features` and `output_margin` param.

Expand All @@ -130,19 +130,19 @@ class SparkXGBClassifier(_SparkXGBEstimator, HasProbabilityCol, HasRawPrediction
callbacks:
The export and import of the callback functions are at best effort. For
details, see :py:attr:`xgboost.spark.SparkXGBClassifier.callbacks` param doc.
rawPredictionCol:
raw_prediction_col:
The `output_margin=True` is implicitly supported by the
`rawPredictionCol` output column, which is always returned with the predicted margin
values.
validationIndicatorCol:
validation_indicator_col:
For params related to `xgboost.XGBClassifier` training with
evaluation dataset's supervision,
set :py:attr:`xgboost.spark.SparkXGBClassifier.validationIndicatorCol`
set :py:attr:`xgboost.spark.SparkXGBClassifier.validation_indicator_col`
parameter instead of setting the `eval_set` parameter in `xgboost.XGBClassifier`
fit method.
weightCol:
weight_col:
To specify the weight of the training and validation dataset, set
:py:attr:`xgboost.spark.SparkXGBClassifier.weightCol` parameter instead of setting
:py:attr:`xgboost.spark.SparkXGBClassifier.weight_col` parameter instead of setting
`sample_weight` and `sample_weight_eval_set` parameter in `xgboost.XGBClassifier`
fit method.
xgb_model:
Expand Down