"SKEWED gamma like Non-negative pdf modeling= poor learner performance"

fritmorefritmore Member Posts: 90  Maven
edited May 23 in Help
Hi

I have noticed that if a label attribute has a  non negative highly skewed distribution the performance of learners such as Neural net is very poor compared to symmetrical (about zero) pdf problems.

Any way to tweak/bias a learner for such a distribution?

thx
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Answers

  • IngoRMIngoRM Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, Community Manager, RMResearcher, Member, University Professor Posts: 1,702  RM Founder
    Hi,

    maybe it helps if you normalize the label before training and de-normalize the prediction after model application... I am not sure if this helps (not using NN a lot myself...)

    Cheers,
    Ingo
    RapidMiner Wisdom 2020
    February 11th and 12th 2020 in Boston, MA, USA

  • fritmorefritmore Member Posts: 90  Maven
    Hi Ingo

    hmm

    I am using nn for it and there is a parameter on the nn operator to normalize the data, it doesnt really help thoug...
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