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Trevor Grant commented on FLINK-1994: ------------------------------------- A little git necromancy here. This issue is done and works more or less as expected with 5 new gain calculations schemes (the two proposed and 3 I lifted from sklearn). This is my first code commit and I need a little guidance. I can add to the docs/website no problem. The testing suite I'm less sure of. I've never written useful integration or unit tests before. There is one new parameter which can take the values 0 through 5. Just would like a little mentoring before I go mucking up the current test. The question is: should I create a pull request now, or do I need to complete the docs AND testing sections before creating the pull request. Thanks in advance.... tg > Add different gain calculation schemes to SGD > --------------------------------------------- > > Key: FLINK-1994 > URL: https://issues.apache.org/jira/browse/FLINK-1994 > Project: Flink > Issue Type: Improvement > Components: Machine Learning Library > Reporter: Till Rohrmann > Assignee: Trevor Grant > Priority: Minor > Labels: ML, Starter > > The current SGD implementation uses as gain for the weight updates the > formula {{stepsize/sqrt(iterationNumber)}}. It would be good to make the gain > calculation configurable and to provide different strategies for that. For > example: > * stepsize/(1 + iterationNumber) > * stepsize*(1 + regularization * stepsize * iterationNumber)^(-3/4) > See also how to properly select the gains [1]. > Resources: > [1] http://arxiv.org/pdf/1107.2490.pdf -- This message was sent by Atlassian JIRA (v6.3.4#6332)