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Apache Spark commented on SPARK-18456: -------------------------------------- User 'sethah' has created a pull request for this issue: https://github.com/apache/spark/pull/15893 > Use matrix abstraction for LogisitRegression coefficients during training > ------------------------------------------------------------------------- > > Key: SPARK-18456 > URL: https://issues.apache.org/jira/browse/SPARK-18456 > Project: Spark > Issue Type: Improvement > Components: ML > Reporter: Seth Hendrickson > Priority: Minor > > This is a follow up from > [SPARK-18060|https://issues.apache.org/jira/browse/SPARK-18060]. The current > code for logistic regression relies on manually indexing flat arrays of > column major coefficients, which can be messy and is hard to maintain. We can > use a matrix abstraction instead of a flat array to simplify things. This > will make the code easier to read and maintain. -- 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