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Sean R. Owen commented on SPARK-29967: -------------------------------------- Yes, I think that is a fine idea, but nothing has really been migrated. For consistency, might be fine to leave the core in .mllib and consider a mass migration later. (If it's not going to make the change unwieldy.) I kind of doubt it'll ever really be moved as there isn't a huge upside to breaking any code using .mllib > KMeans support instance weighting > --------------------------------- > > Key: SPARK-29967 > URL: https://issues.apache.org/jira/browse/SPARK-29967 > Project: Spark > Issue Type: Improvement > Components: ML, PySpark > Affects Versions: 3.0.0 > Reporter: zhengruifeng > Priority: Major > > Since https://issues.apache.org/jira/browse/SPARK-9610, we start to support > instance weighting in ML. > However, Clustering and other impl in features still do not support instance > weighting. > I think we need to start support weighting in KMeans, like what scikit-learn > does. > It will contains three parts: > 1, move the impl from .mllib to .ml > 2, make .mllib.KMeans as a wrapper of .ml.KMeans > 3, support instance weighting in the .ml.KMeans -- This message was sent by Atlassian Jira (v8.3.4#803005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org