Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16028#discussion_r124730326
--- Diff: python/pyspark/ml/classification.py ---
@@ -1327,8 +1327,6 @@ class MultilayerPerceptronClassifier(JavaEstimator,
HasFeaturesCol, HasLabelCol,
"remaining data in a partition then it is adjusted
to the size of this " +
"data. Recommended size is between 10 and 1000,
default is 128.",
typeConverter=TypeConverters.toInt)
- solver = Param(Params._dummy(), "solver", "The solver algorithm for
optimization. Supported " +
--- End diff --
We still need to print out supported options for different algorithms, so
could we override param definition in Python as well as what we did in Scala?
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