AUPRC

DocMusherDocMusher Member Posts: 249   Unicorn
edited November 2018 in Help
Who is able to help us.
It eems that we will have to implement AUPRC for the paper (because all papers in PLOS I are using this measure in case of inballanced data).

I tried to do it with R extension, and succeded to evaluate models, but I cannot use it in optimization and validation of models (because execute R cannot provide object "averagable" that is used in X-validation).

So I wanted to implement AUPRC as new operator, but I cannot find source code of RM6.5. Is it still open? and if it is where can I find it.

Or if you have some other way to include AUPRC in process please tell me.

Sven and Milan
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Answers

  • Marco_BoeckMarco_Boeck Team Lead Software Engineering Moderator, Employee, Member, University Professor Posts: 1,806   RM Engineering
    Hi,

    as of Studio 6.5, the core has been released once more under AGPL3. The sources can be found by either clicking the "Source Download" link on the actual download page of RapidMiner Studio or by simply clicking here: https://github.com/rapidminer/rapidminer-studio

    Regards,
    Marco
  • mschmitzmschmitz Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, University Professor Posts: 2,107  RM Data Scientist
    Hi sven,

    i responded by mail, but for all of you:
    Extract Performance solves the problem. You can generate any performance value in R/Python and them convert the example set into an RM Performance vector with this operator.


    Yours,
    Martin
    - Head of Data Science Services at RapidMiner -
    Dortmund, Germany
  • Milan_VukicevicMilan_Vukicevic RapidMiner Certified Expert, Member Posts: 1 Contributor I
    Thank you all

    This is solved
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