diff options
| -rw-r--r-- | python/pyspark/ml/param/_shared_params_code_gen.py | 6 | ||||
| -rw-r--r-- | python/pyspark/ml/param/shared.py | 30 | ||||
| -rw-r--r-- | python/pyspark/ml/tests.py | 4 | ||||
| -rw-r--r-- | tox.ini | 2 |
4 files changed, 20 insertions, 22 deletions
diff --git a/python/pyspark/ml/param/_shared_params_code_gen.py b/python/pyspark/ml/param/_shared_params_code_gen.py index ed3171b697..3be0979b92 100644 --- a/python/pyspark/ml/param/_shared_params_code_gen.py +++ b/python/pyspark/ml/param/_shared_params_code_gen.py @@ -88,12 +88,12 @@ if __name__ == "__main__": print("\n# DO NOT MODIFY THIS FILE! It was generated by _shared_params_code_gen.py.\n") print("from pyspark.ml.param import Param, Params\n\n") shared = [ - ("maxIter", "max number of iterations", None), - ("regParam", "regularization constant", None), + ("maxIter", "max number of iterations (>= 0)", None), + ("regParam", "regularization parameter (>= 0)", None), ("featuresCol", "features column name", "'features'"), ("labelCol", "label column name", "'label'"), ("predictionCol", "prediction column name", "'prediction'"), - ("rawPredictionCol", "raw prediction column name", "'rawPrediction'"), + ("rawPredictionCol", "raw prediction (a.k.a. confidence) column name", "'rawPrediction'"), ("inputCol", "input column name", None), ("inputCols", "input column names", None), ("outputCol", "output column name", None), diff --git a/python/pyspark/ml/param/shared.py b/python/pyspark/ml/param/shared.py index d0bcadee22..4b22322b89 100644 --- a/python/pyspark/ml/param/shared.py +++ b/python/pyspark/ml/param/shared.py @@ -22,16 +22,16 @@ from pyspark.ml.param import Param, Params class HasMaxIter(Params): """ - Mixin for param maxIter: max number of iterations. + Mixin for param maxIter: max number of iterations (>= 0). """ # a placeholder to make it appear in the generated doc - maxIter = Param(Params._dummy(), "maxIter", "max number of iterations") + maxIter = Param(Params._dummy(), "maxIter", "max number of iterations (>= 0)") def __init__(self): super(HasMaxIter, self).__init__() - #: param for max number of iterations - self.maxIter = Param(self, "maxIter", "max number of iterations") + #: param for max number of iterations (>= 0) + self.maxIter = Param(self, "maxIter", "max number of iterations (>= 0)") if None is not None: self._setDefault(maxIter=None) @@ -51,16 +51,16 @@ class HasMaxIter(Params): class HasRegParam(Params): """ - Mixin for param regParam: regularization constant. + Mixin for param regParam: regularization parameter (>= 0). """ # a placeholder to make it appear in the generated doc - regParam = Param(Params._dummy(), "regParam", "regularization constant") + regParam = Param(Params._dummy(), "regParam", "regularization parameter (>= 0)") def __init__(self): super(HasRegParam, self).__init__() - #: param for regularization constant - self.regParam = Param(self, "regParam", "regularization constant") + #: param for regularization parameter (>= 0) + self.regParam = Param(self, "regParam", "regularization parameter (>= 0)") if None is not None: self._setDefault(regParam=None) @@ -167,16 +167,16 @@ class HasPredictionCol(Params): class HasRawPredictionCol(Params): """ - Mixin for param rawPredictionCol: raw prediction column name. + Mixin for param rawPredictionCol: raw prediction (a.k.a. confidence) column name. """ # a placeholder to make it appear in the generated doc - rawPredictionCol = Param(Params._dummy(), "rawPredictionCol", "raw prediction column name") + rawPredictionCol = Param(Params._dummy(), "rawPredictionCol", "raw prediction (a.k.a. confidence) column name") def __init__(self): super(HasRawPredictionCol, self).__init__() - #: param for raw prediction column name - self.rawPredictionCol = Param(self, "rawPredictionCol", "raw prediction column name") + #: param for raw prediction (a.k.a. confidence) column name + self.rawPredictionCol = Param(self, "rawPredictionCol", "raw prediction (a.k.a. confidence) column name") if 'rawPrediction' is not None: self._setDefault(rawPredictionCol='rawPrediction') @@ -403,14 +403,12 @@ class HasStepSize(Params): """ # a placeholder to make it appear in the generated doc - stepSize = Param(Params._dummy(), "stepSize", - "Step size to be used for each iteration of optimization.") + stepSize = Param(Params._dummy(), "stepSize", "Step size to be used for each iteration of optimization.") def __init__(self): super(HasStepSize, self).__init__() #: param for Step size to be used for each iteration of optimization. - self.stepSize = Param(self, "stepSize", - "Step size to be used for each iteration of optimization.") + self.stepSize = Param(self, "stepSize", "Step size to be used for each iteration of optimization.") if None is not None: self._setDefault(stepSize=None) diff --git a/python/pyspark/ml/tests.py b/python/pyspark/ml/tests.py index 75bb5d749c..ba6478dcd5 100644 --- a/python/pyspark/ml/tests.py +++ b/python/pyspark/ml/tests.py @@ -128,7 +128,7 @@ class ParamTests(PySparkTestCase): testParams = TestParams() maxIter = testParams.maxIter self.assertEqual(maxIter.name, "maxIter") - self.assertEqual(maxIter.doc, "max number of iterations") + self.assertEqual(maxIter.doc, "max number of iterations (>= 0)") self.assertTrue(maxIter.parent is testParams) def test_params(self): @@ -156,7 +156,7 @@ class ParamTests(PySparkTestCase): self.assertEquals( testParams.explainParams(), "\n".join(["inputCol: input column name (undefined)", - "maxIter: max number of iterations (default: 10, current: 100)"])) + "maxIter: max number of iterations (>= 0) (default: 10, current: 100)"])) if __name__ == "__main__": @@ -15,4 +15,4 @@ [pep8] max-line-length=100 -exclude=cloudpickle.py,heapq3.py +exclude=cloudpickle.py,heapq3.py,shared.py |