diff options
Diffstat (limited to 'python/pyspark/ml/tuning.py')
| -rw-r--r-- | python/pyspark/ml/tuning.py | 26 |
1 files changed, 13 insertions, 13 deletions
diff --git a/python/pyspark/ml/tuning.py b/python/pyspark/ml/tuning.py index ea8c61b7ef..456d79d897 100644 --- a/python/pyspark/ml/tuning.py +++ b/python/pyspark/ml/tuning.py @@ -24,7 +24,7 @@ from pyspark.ml import Estimator, Model from pyspark.ml.param import Params, Param, TypeConverters from pyspark.ml.param.shared import HasSeed from pyspark.ml.util import keyword_only, JavaMLWriter, JavaMLReader, MLReadable, MLWritable -from pyspark.ml.wrapper import JavaWrapper +from pyspark.ml.wrapper import JavaParams from pyspark.sql.functions import rand from pyspark.mllib.common import inherit_doc, _py2java @@ -148,8 +148,8 @@ class ValidatorParams(HasSeed): """ # Load information from java_stage to the instance. - estimator = JavaWrapper._from_java(java_stage.getEstimator()) - evaluator = JavaWrapper._from_java(java_stage.getEvaluator()) + estimator = JavaParams._from_java(java_stage.getEstimator()) + evaluator = JavaParams._from_java(java_stage.getEvaluator()) epms = [estimator._transfer_param_map_from_java(epm) for epm in java_stage.getEstimatorParamMaps()] return estimator, epms, evaluator @@ -329,7 +329,7 @@ class CrossValidator(Estimator, ValidatorParams, MLReadable, MLWritable): estimator, epms, evaluator = super(CrossValidator, self)._to_java_impl() - _java_obj = JavaWrapper._new_java_obj("org.apache.spark.ml.tuning.CrossValidator", self.uid) + _java_obj = JavaParams._new_java_obj("org.apache.spark.ml.tuning.CrossValidator", self.uid) _java_obj.setEstimatorParamMaps(epms) _java_obj.setEvaluator(evaluator) _java_obj.setEstimator(estimator) @@ -393,7 +393,7 @@ class CrossValidatorModel(Model, ValidatorParams, MLReadable, MLWritable): """ # Load information from java_stage to the instance. - bestModel = JavaWrapper._from_java(java_stage.bestModel()) + bestModel = JavaParams._from_java(java_stage.bestModel()) estimator, epms, evaluator = super(CrossValidatorModel, cls)._from_java_impl(java_stage) # Create a new instance of this stage. py_stage = cls(bestModel=bestModel)\ @@ -410,10 +410,10 @@ class CrossValidatorModel(Model, ValidatorParams, MLReadable, MLWritable): sc = SparkContext._active_spark_context - _java_obj = JavaWrapper._new_java_obj("org.apache.spark.ml.tuning.CrossValidatorModel", - self.uid, - self.bestModel._to_java(), - _py2java(sc, [])) + _java_obj = JavaParams._new_java_obj("org.apache.spark.ml.tuning.CrossValidatorModel", + self.uid, + self.bestModel._to_java(), + _py2java(sc, [])) estimator, epms, evaluator = super(CrossValidatorModel, self)._to_java_impl() _java_obj.set("evaluator", evaluator) @@ -574,8 +574,8 @@ class TrainValidationSplit(Estimator, ValidatorParams, MLReadable, MLWritable): estimator, epms, evaluator = super(TrainValidationSplit, self)._to_java_impl() - _java_obj = JavaWrapper._new_java_obj("org.apache.spark.ml.tuning.TrainValidationSplit", - self.uid) + _java_obj = JavaParams._new_java_obj("org.apache.spark.ml.tuning.TrainValidationSplit", + self.uid) _java_obj.setEstimatorParamMaps(epms) _java_obj.setEvaluator(evaluator) _java_obj.setEstimator(estimator) @@ -639,7 +639,7 @@ class TrainValidationSplitModel(Model, ValidatorParams, MLReadable, MLWritable): """ # Load information from java_stage to the instance. - bestModel = JavaWrapper._from_java(java_stage.bestModel()) + bestModel = JavaParams._from_java(java_stage.bestModel()) estimator, epms, evaluator = \ super(TrainValidationSplitModel, cls)._from_java_impl(java_stage) # Create a new instance of this stage. @@ -657,7 +657,7 @@ class TrainValidationSplitModel(Model, ValidatorParams, MLReadable, MLWritable): sc = SparkContext._active_spark_context - _java_obj = JavaWrapper._new_java_obj( + _java_obj = JavaParams._new_java_obj( "org.apache.spark.ml.tuning.TrainValidationSplitModel", self.uid, self.bestModel._to_java(), |