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How to customize number of hidden layers and number of Neurons in Neural Nets using Rapidminer?

vjmeenavjmeena Member Posts: 5 Newbie
Is there a way to customize number of hidden layers and number of Neurons in Neural Nets using Rapidminer?

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  • mbsmbs Member Posts: 120  Guru
    @varunm1
    hi
    the result of your suggestion is good for deep learning but for neural network it is not that much ok. also neural network has so many problems itself and i have to delete most of the row of data :/
  • varunm1varunm1 Member Posts: 442   Unicorn
    edited May 14
    Hello @mbs

    Sorry, I didn't get your point. Can you please explain in detail? What is the issue you are facing? 
    Regards,
    Varun
    mbs
  • mbsmbs Member Posts: 120  Guru
    @varunm1
    according to your solution in this post I try to make less hidden layers with deep learning and also i did it for neural network but neural network most of the time show that my data has missing value in different parts but really my data is clean and it doesnt have any missing part so even with changing the setting of that i have to remove some parts of my data and even in this situation accuracy is around 50%
    regards
    mbs
  • varunm1varunm1 Member Posts: 442   Unicorn
    The solution here just refers to customizing hidden layers with neurons in a neural network operator and nothing related to the performance of networks. 

    The deep learning operator is more customizable with different activation functions (that can be chosen) etc. They are much more complex compared to a simple neural net which is the reason you might get better results. Coming to the issue related to missing values, it's difficult to understand unless I see the data and your XML. Also, deep learning operator handles missing values (you can see in parameters) by either imputing or skipping them which might be the reason you are not getting an error.

    Thanks
    Regards,
    Varun
    mbsdbabrauskaite
  • mbsmbs Member Posts: 120  Guru
    @varunm1
    thank you for your recommendation
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