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Diffstat (limited to 'python/pyspark/ml/tuning.py')
| -rw-r--r-- | python/pyspark/ml/tuning.py | 18 |
1 files changed, 0 insertions, 18 deletions
diff --git a/python/pyspark/ml/tuning.py b/python/pyspark/ml/tuning.py index 08f8db57f4..0cbe97f1d8 100644 --- a/python/pyspark/ml/tuning.py +++ b/python/pyspark/ml/tuning.py @@ -115,18 +115,11 @@ class CrossValidator(Estimator, HasSeed): .. versionadded:: 1.4.0 """ - # a placeholder to make it appear in the generated doc estimator = Param(Params._dummy(), "estimator", "estimator to be cross-validated") - - # a placeholder to make it appear in the generated doc estimatorParamMaps = Param(Params._dummy(), "estimatorParamMaps", "estimator param maps") - - # a placeholder to make it appear in the generated doc evaluator = Param( Params._dummy(), "evaluator", "evaluator used to select hyper-parameters that maximize the cross-validated metric") - - # a placeholder to make it appear in the generated doc numFolds = Param(Params._dummy(), "numFolds", "number of folds for cross validation") @keyword_only @@ -137,17 +130,6 @@ class CrossValidator(Estimator, HasSeed): seed=None) """ super(CrossValidator, self).__init__() - #: param for estimator to be cross-validated - self.estimator = Param(self, "estimator", "estimator to be cross-validated") - #: param for estimator param maps - self.estimatorParamMaps = Param(self, "estimatorParamMaps", "estimator param maps") - #: param for the evaluator used to select hyper-parameters that - #: maximize the cross-validated metric - self.evaluator = Param( - self, "evaluator", - "evaluator used to select hyper-parameters that maximize the cross-validated metric") - #: param for number of folds for cross validation - self.numFolds = Param(self, "numFolds", "number of folds for cross validation") self._setDefault(numFolds=3) kwargs = self.__init__._input_kwargs self._set(**kwargs) |