Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/5707#discussion_r29821470
--- Diff: python/pyspark/mllib/util.py ---
@@ -169,6 +169,14 @@ def loadLabeledPoints(sc, path, minPartitions=None):
minPartitions = minPartitions or min(sc.defaultParallelism, 2)
return callMLlibFunc("loadLabeledPoints", sc, path, minPartitions)
+ @staticmethod
+ def appendBias(data):
--- End diff --
Since the Scala version only operates on individual vectors, this one
should not be a wrapper; it should do everything in Python. The reason is that
callMLlibFunc requires the SparkContext and needs to operate on the driver.
But since appendBias operates per-Row, it needs to be called on workers.
Also, please add doc. Feel free to copy from Scala doc.
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