srowen commented on code in PR #38996: URL: https://github.com/apache/spark/pull/38996#discussion_r1044938891
########## docs/mllib-isotonic-regression.md: ########## @@ -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: (Sorry if this double-posts) Yeah I was confused about this too. If feature values are pooled when exactly equal, why average them? if anything that introduces tiny errors -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
