Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/8214#discussion_r41445907
--- Diff: python/pyspark/ml/regression.py ---
@@ -142,6 +143,122 @@ def intercept(self):
return self._call_java("intercept")
+@inherit_doc
+class IsotonicRegression(JavaEstimator, HasFeaturesCol, HasLabelCol,
HasPredictionCol,
+ HasWeightCol):
+ """
+ Currently implemented using parallelized pool adjacent violators
algorithm.
+ Only univariate (single feature) algorithm supported.
+
+ >>> from pyspark.mllib.linalg import Vectors
+ >>> df = sqlContext.createDataFrame([
+ ... (1.0, Vectors.dense(1.0)),
+ ... (0.0, Vectors.sparse(1, [], []))], ["label", "features"])
+ >>> ir = IsotonicRegression()
+ >>> ir.getIsotonic()
--- End diff --
I'd remove this. It's confusing (and this is part of the documentation).
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