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| author | Liang-Chi Hsieh <simonh@tw.ibm.com> | 2016-05-20 13:40:13 +0200 |
|---|---|---|
| committer | Nick Pentreath <nickp@za.ibm.com> | 2016-05-20 13:40:13 +0200 |
| commit | 4e739331187f2acdd84a5e65857edb62e58a0f8f (patch) | |
| tree | 748d7e34aa037b149f9dddb2900c9a13f994b20b /python/pyspark/ml | |
| parent | c32b1b162e7e5ecc5c823f79ba9f23cbd1407dbf (diff) | |
| download | spark-4e739331187f2acdd84a5e65857edb62e58a0f8f.tar.gz spark-4e739331187f2acdd84a5e65857edb62e58a0f8f.tar.bz2 spark-4e739331187f2acdd84a5e65857edb62e58a0f8f.zip | |
[SPARK-15444][PYSPARK][ML][HOTFIX] Default value mismatch of param linkPredictionCol for GeneralizedLinearRegression
## What changes were proposed in this pull request?
Default value mismatch of param linkPredictionCol for GeneralizedLinearRegression between PySpark and Scala. That is because default value conflict between #13106 and #13129. This causes ml.tests failed.
## How was this patch tested?
Existing tests.
Author: Liang-Chi Hsieh <simonh@tw.ibm.com>
Closes #13220 from viirya/hotfix-regresstion.
Diffstat (limited to 'python/pyspark/ml')
| -rw-r--r-- | python/pyspark/ml/regression.py | 11 |
1 files changed, 5 insertions, 6 deletions
diff --git a/python/pyspark/ml/regression.py b/python/pyspark/ml/regression.py index 25640b1f85..e21dd83923 100644 --- a/python/pyspark/ml/regression.py +++ b/python/pyspark/ml/regression.py @@ -1303,17 +1303,16 @@ class GeneralizedLinearRegression(JavaEstimator, HasLabelCol, HasFeaturesCol, Ha @keyword_only def __init__(self, labelCol="label", featuresCol="features", predictionCol="prediction", family="gaussian", link=None, fitIntercept=True, maxIter=25, tol=1e-6, - regParam=0.0, weightCol=None, solver="irls", linkPredictionCol=""): + regParam=0.0, weightCol=None, solver="irls", linkPredictionCol=None): """ __init__(self, labelCol="label", featuresCol="features", predictionCol="prediction", \ family="gaussian", link=None, fitIntercept=True, maxIter=25, tol=1e-6, \ - regParam=0.0, weightCol=None, solver="irls", linkPredictionCol="") + regParam=0.0, weightCol=None, solver="irls", linkPredictionCol=None) """ super(GeneralizedLinearRegression, self).__init__() self._java_obj = self._new_java_obj( "org.apache.spark.ml.regression.GeneralizedLinearRegression", self.uid) - self._setDefault(family="gaussian", maxIter=25, tol=1e-6, regParam=0.0, solver="irls", - linkPredictionCol="") + self._setDefault(family="gaussian", maxIter=25, tol=1e-6, regParam=0.0, solver="irls") kwargs = self.__init__._input_kwargs self.setParams(**kwargs) @@ -1321,11 +1320,11 @@ class GeneralizedLinearRegression(JavaEstimator, HasLabelCol, HasFeaturesCol, Ha @since("2.0.0") def setParams(self, labelCol="label", featuresCol="features", predictionCol="prediction", family="gaussian", link=None, fitIntercept=True, maxIter=25, tol=1e-6, - regParam=0.0, weightCol=None, solver="irls", linkPredictionCol=""): + regParam=0.0, weightCol=None, solver="irls", linkPredictionCol=None): """ setParams(self, labelCol="label", featuresCol="features", predictionCol="prediction", \ family="gaussian", link=None, fitIntercept=True, maxIter=25, tol=1e-6, \ - regParam=0.0, weightCol=None, solver="irls", linkPredictionCol="") + regParam=0.0, weightCol=None, solver="irls", linkPredictionCol=None) Sets params for generalized linear regression. """ kwargs = self.setParams._input_kwargs |