From 4e739331187f2acdd84a5e65857edb62e58a0f8f Mon Sep 17 00:00:00 2001
From: Liang-Chi Hsieh <simonh@tw.ibm.com>
Date: Fri, 20 May 2016 13:40:13 +0200
Subject: [PATCH] [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.
---
python/pyspark/ml/regression.py | 11 +++++------
1 file 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
--
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