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Advantages of MRMR

noritanorita Member Posts: 29 Contributor I
I chose MRMR selection for the first selection and then forward selection as further selection for my model. Now I want to justify my choice.
So far, I would say MRMR is not expensive in compution time and therefor good for a first selection (150 variables). And it is better as other filter methods (also computional inexpensive methods) as e.g select by weight by correlation /information gain because it adresses the interferance of variables amongst each other.

What do you think of my reasoning? Is there an advantage of the MRMR algorithm I missed? Are there any recommondations where it is likely to use?



Best Answer

  • mschmitzmschmitz Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, University Professor Posts: 3,078  RM Data Scientist
    Solution Accepted
    Hi @norita ,
    for me there is a tradeoff between the runtime/complexity of the algorithm. I quickly drew how i think the power/rumtime tradeoff looks like


    So MRMR is actually a nice tradeoff here. But you are right it is not perfect. I also often use it as a pre-filter to go down to a handable sample size first.

    Cheers,
    Martin

    - Head of Data Science Services at RapidMiner -
    Dortmund, Germany
    ceapereznorita

Answers

  • noritanorita Member Posts: 29 Contributor I
    Thank you very much! Nice graph!:)
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