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Multi-objective Optimization for Feature Selection

Asaber_07Asaber_07 Member Posts: 1 Learner I
in Help
thank you for the tutorial 

Multi-objective Optimization for Feature Selection

 I much appreciated, just a single question in the structural risk ie the number of features chosen what is its formula in terms of programming is what we do a ration the number chosen on the total number features ?? conceming the term C: trade off factor, its the interval between 0 and 1 ?? Thanks again

Answers

  • sgenzersgenzer Administrator, Moderator, Employee-RapidMiner, RapidMiner Certified Analyst, Community Manager, Member, University Professor, PM Moderator Posts: 2,959 Community Manager
    cc'ing MOFS maestro @IngoRM
  • IngoRMIngoRM Employee-RapidMiner, RapidMiner Certified Analyst, RapidMiner Certified Expert, Community Manager, RMResearcher, Member, University Professor Posts: 1,751 RM Founder
    Hi,
    just a single question in the structural risk ie the number of features chosen what is its formula in terms of programming is what we do a ration the number chosen on the total number features?
    While you could do this that way, this would only work well for feature selection, not for feature construction.  A good way to support both feature engineering tasks is simply to use the sum of features as the risk calculation.  This works well since the multi-objective optimizations does not care about the scale of the criterion at all and also does not need any trade-off parameters.

    conceming the term C: trade off factor, its the interval between 0 and 1 ?
    No, the range is unrestricted between 0 and infinite.  However, one of the beautiful things about a multi-objective regularization approach is that you actually do not need any C at all in the first place :-)

    Hope this helps,
    Ingo
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