ahmed-mahran commented on code in PR #38996:
URL: https://github.com/apache/spark/pull/38996#discussion_r1045202051


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docs/mllib-isotonic-regression.md:
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@@ -43,7 +43,17 @@ best fitting the original data points.
 which uses an approach to
 [parallelizing isotonic 
regression](https://doi.org/10.1007/978-3-642-99789-1_10).
 The training input is an RDD of tuples of three double values that represent
-label, feature and weight in this order. Additionally, IsotonicRegression 
algorithm has one
+label, feature and weight in this order. In case there are multiple tuples with
+the same feature then these tuples are aggregated into a single tuple as 
follows:
+
+* Aggregated label is the weighted average of all labels.
+* Aggregated feature is the weighted average of all equal features. It is 
possible

Review Comment:
   Now it is exact equality likewise other parts of the implementation that 
don't handle approximation errors, and it should be the responsibility of the 
user to handle such cases before fitting the model.



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