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Patrick Wendell commented on SPARK-3188: ---------------------------------------- Hey [~fjiang6] please don't set the fix version on an issue until it is actually merged. Also, in general this field set by the committers and not contributors. > Add Robust Regression Algorithm with Tukey bisquare weight function > (Biweight Estimates) > ------------------------------------------------------------------------------------------ > > Key: SPARK-3188 > URL: https://issues.apache.org/jira/browse/SPARK-3188 > Project: Spark > Issue Type: New Feature > Components: MLlib > Affects Versions: 1.0.2 > Reporter: Fan Jiang > Priority: Critical > Labels: features > Original Estimate: 0h > Remaining Estimate: 0h > > Linear least square estimates assume the error has normal distribution and > can behave badly when the errors are heavy-tailed. In practical we get > various types of data. We need to include Robust Regression to employ a > fitting criterion that is not as vulnerable as least square. > The Tukey bisquare weight function, also referred to as the biweight > function, produces an M-estimator that is more resistant to regression > outliers than the Huber M-estimator (Andersen 2008: 19). -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org