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| author | Holden Karau <holden@us.ibm.com> | 2016-01-26 15:53:48 -0800 |
|---|---|---|
| committer | Joseph K. Bradley <joseph@databricks.com> | 2016-01-26 15:53:48 -0800 |
| commit | eb917291ca1a2d68ca0639cb4b1464a546603eba (patch) | |
| tree | 380dcaa33273baa68beaf089387bd498d5ee88e8 /python/pyspark/ml/tuning.py | |
| parent | 19fdb21afbf0eae4483cf6d4ef32daffd1994b89 (diff) | |
| download | spark-eb917291ca1a2d68ca0639cb4b1464a546603eba.tar.gz spark-eb917291ca1a2d68ca0639cb4b1464a546603eba.tar.bz2 spark-eb917291ca1a2d68ca0639cb4b1464a546603eba.zip | |
[SPARK-10509][PYSPARK] Reduce excessive param boiler plate code
The current python ml params require cut-and-pasting the param setup and description between the class & ```__init__``` methods. Remove this possible case of errors & simplify use of custom params by adding a ```_copy_new_parent``` method to param so as to avoid cut and pasting (and cut and pasting at different indentation levels urgh).
Author: Holden Karau <holden@us.ibm.com>
Closes #10216 from holdenk/SPARK-10509-excessive-param-boiler-plate-code.
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) |