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From: MLnick <git@git.apache.org>
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Subject: [GitHub] spark pull request: [SPARK-15139][SPARK-15092][PYSPARK][ML]
 Pyspar...
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Message-Id: <20160505174900.6F2B3DFE16@git1-us-west.apache.org>
Date: Thu,  5 May 2016 17:49:00 +0000 (UTC)

Github user MLnick commented on a diff in the pull request:

    https://github.com/apache/spark/pull/12919#discussion_r62224930
  
    --- Diff: python/pyspark/ml/regression.py ---
    @@ -743,6 +743,18 @@ def treeWeights(self):
             """Return the weights for each tree"""
             return list(self._call_java("javaTreeWeights"))
     
    +    @property
    --- End diff --
    
    Yeah - may as well leave it for now. Perhaps later it may make sense to
    refactor it into one of the traits for Scala and Python
    
    On Thu, 5 May 2016 at 17:22, Seth Hendrickson <notifications@github.com>
    wrote:
    
    > In python/pyspark/ml/regression.py
    > <https://github.com/apache/spark/pull/12919#discussion_r62202569>:
    >
    > > @@ -743,6 +743,18 @@ def treeWeights(self):
    > >          """Return the weights for each tree"""
    > >          return list(self._call_java("javaTreeWeights"))
    > >
    > > +    @property
    >
    > This question applies to Scala API as well. Partly, I think, because in
    > the Scala API things were done incrementally. But also because there may be
    > some hope in the future that more predictors provide feature importances,
    > and then it could be an abstract method in the Predictor class instead. I
    > don't know that there's a better reason.
    >
    > —
    > You are receiving this because you commented.
    > Reply to this email directly or view it on GitHub
    > <https://github.com/apache/spark/pull/12919/files/6400e9e3d7e096b05475cca548e31aabca8cbaff#r62202569>
    >


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