Github user jkbradley commented on the pull request:
https://github.com/apache/spark/pull/11621#issuecomment-207048048
Good point, let's expose the solver for now. I made a JIRA:
https://issues.apache.org/jira/browse/SPARK-14461
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Github user BryanCutler commented on the pull request:
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So if we included something like the following in an example, it should be
clear what's happening
```Scala
val trainingSummary = lrModel.summary
tra
Github user BryanCutler commented on the pull request:
https://github.com/apache/spark/pull/11621#issuecomment-207004666
@jkbradley, adding those methods would make it a little more usable I
think. Another option might be to just add a method to return the solver used,
and then the u
Github user jkbradley commented on the pull request:
https://github.com/apache/spark/pull/11621#issuecomment-206566624
By the way, what do you think about providing methods to test if data are
available?
E.g.,
```
/** Indicates if [[coefficientStandardErrors()]] is availabl
Github user jkbradley commented on the pull request:
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LGTM
Merging with master
Thanks very much!
Could you please create a JIRA for updating JavaWrapper and JavaCallable?
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Github user BryanCutler commented on the pull request:
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Cool, thanks!
> Could you please create a JIRA for updating JavaWrapper and JavaCallable?
Will do
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--- Diff:
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@@ -777,10 +777,10 @@ sealed trait LogisticRegressionSummar
Github user BryanCutler commented on the pull request:
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@jkbradley I incorporated the latest feedback, please take another look
when you get a chance, thanks!
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jenkins retest this please
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Github user jkbradley commented on the pull request:
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@BryanCutler Thanks for the updates! They look good. I just commented on
some of the discussions above.
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--- Diff: python/pyspark/ml/regression.py ---
@@ -151,6 +151,228 @@ def intercept(self):
"""
return self._call_java("intercept")
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--- Diff: python/pyspark/ml/regression.py ---
@@ -151,6 +151,209 @@ def intercept(self):
"""
return self._call_java("intercept")
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--- Diff: python/pyspark/ml/tests.py ---
@@ -238,6 +238,17 @@ def setParams(self, seed=None):
return self._set(**kwargs)
+class
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--- Diff:
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@@ -539,6 +539,10 @@ class LinearRegressionTrainingSummary
privat
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--- Diff: python/pyspark/ml/wrapper.py ---
@@ -190,8 +190,30 @@ def _transform(self, dataset):
return DataFrame(self._java_obj.transform(datase
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--- Diff: python/pyspark/ml/regression.py ---
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"""
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--- Diff: python/pyspark/ml/regression.py ---
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"""
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--- Diff: python/pyspark/ml/tests.py ---
@@ -238,6 +238,17 @@ def setParams(self, seed=None):
return self._set(**kwargs)
+cla
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--- Diff: python/pyspark/ml/wrapper.py ---
@@ -190,8 +190,30 @@ def _transform(self, dataset):
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--- Diff: python/pyspark/ml/regression.py ---
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--- Diff: python/pyspark/ml/regression.py ---
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--- Diff: python/pyspark/ml/regression.py ---
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"""
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Github user jkbradley commented on the pull request:
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I had several minor comments, and there were 2 missing methods. Otherwise,
it's looking good.
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--- Diff: python/pyspark/ml/regression.py ---
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--- Diff: python/pyspark/ml/regression.py ---
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--- Diff: python/pyspark/ml/classification.py ---
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"""
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--- Diff: python/pyspark/ml/classification.py ---
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--- Diff: python/pyspark/ml/classification.py ---
@@ -28,6 +28,7 @@
__all__ = ['LogisticRegression', 'LogisticRegressionModel',
+
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--- Diff: python/pyspark/ml/classification.py ---
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--- Diff: python/pyspark/ml/classification.py ---
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--- Diff: python/pyspark/ml/classification.py ---
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--- Diff: python/pyspark/ml/classification.py ---
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--- Diff: python/pyspark/ml/classification.py ---
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--- Diff: python/pyspark/ml/wrapper.py ---
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Made `JavaModel` inherit `JavaCallable`, please take a look when you get a
chance @jkbradley and see if this change is ok, thanks!
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@BryanCutler thanks for the PR, I only have a few small comments
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--- Diff: python/pyspark/ml/wrapper.py ---
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__metaclass__ = ABCMeta
-#: The wra
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--- Diff: python/pyspark/mllib/common.py ---
@@ -130,20 +130,39 @@ def callMLlibFunc(name, *args):
return callJavaFunc(sc, api, *args)
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GitHub user BryanCutler opened a pull request:
https://github.com/apache/spark/pull/11621
[SPARK-13430][PySpark][ML] Python API for training summaries of linear and
logistic regression
## What changes were proposed in this pull request?
Adding Python API for training summar
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