Hendrik/xgboost
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Fix feature types param (#8772)

Browse Source 
Signed-off-by: Weichen Xu <weichen.xu@databricks.com>
This commit is contained in:
WeichenXu 2023-02-14 02:16:42 +08:00 committed by GitHub
parent 52d0230b58
commit f27a7258c6
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 12 additions and 1 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

13
python-package/xgboost/spark/core.py
View File

@ -143,6 +143,12 @@ _unsupported_predict_params = {
"base_margin", # Use pyspark base_margin_col param instead. "base_margin", # Use pyspark base_margin_col param instead.
} }
# TODO: supply hint message for all other unsupported params.
_unsupported_params_hint_message = {
"enable_categorical": "`xgboost.spark` estimators do not have 'enable_categorical' param, "
"but you can set `feature_types` param and mark categorical features with 'c' string."
}
# Global prediction names # Global prediction names
Pred = namedtuple( Pred = namedtuple(
"Pred", ("prediction", "raw_prediction", "probability", "pred_contrib") "Pred", ("prediction", "raw_prediction", "probability", "pred_contrib")
@ -540,7 +546,10 @@ class _SparkXGBEstimator(Estimator, _SparkXGBParams, MLReadable, MLWritable):
or k in _unsupported_predict_params or k in _unsupported_predict_params
or k in _unsupported_train_params or k in _unsupported_train_params
): ):
raise ValueError(f"Unsupported param '{k}'.") err_msg = _unsupported_params_hint_message.get(
k, f"Unsupported param '{k}'."
)
raise ValueError(err_msg)
_extra_params[k] = v _extra_params[k] = v
_existing_extra_params = self.getOrDefault(self.arbitrary_params_dict) _existing_extra_params = self.getOrDefault(self.arbitrary_params_dict)
self._set(arbitrary_params_dict={**_existing_extra_params, **_extra_params}) self._set(arbitrary_params_dict={**_existing_extra_params, **_extra_params})
@ -780,6 +789,8 @@ class _SparkXGBEstimator(Estimator, _SparkXGBParams, MLReadable, MLWritable):
"feature_weights": self.getOrDefault(self.feature_weights), "feature_weights": self.getOrDefault(self.feature_weights),
"missing": float(self.getOrDefault(self.missing)), "missing": float(self.getOrDefault(self.missing)),
} }
if dmatrix_kwargs["feature_types"] is not None:
dmatrix_kwargs["enable_categorical"] = True
booster_params["nthread"] = cpu_per_task booster_params["nthread"] = cpu_per_task
# Remove the parameters whose value is None # Remove the parameters whose value is None