How to optimize parameter in linear Regression?

olafansau55
olafansau55 New Altair Community Member
edited November 5 in Community Q&A
hello!!
I create a multiple linear regression model by doing hyperparameter tuning using the operator optimize parameter, but I'm confused about what hyperparameters I should optimize in the rapid miner to avoid overfitting?

I hope someone can help me in solving this problem.
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Answers

  • Marco_Barradas
    Marco_Barradas
    Altair Employee
    Hi @olafansau55

    To avoid overfitting you should always split your data, we usually recommend to use Cross Validation that way you are sure that the model is able to generalize in the best way.

    You can check the hows and why in this video


    Cross Validation and model performance| RapidMiner Studio

  • olafansau55
    olafansau55 New Altair Community Member
    thankyou @MarcoBarradas for reacting to my question. I have done it to do that way, but it still overfitting. did you know what hyperparameter can I use to optimize linear regression? and what is the ridge parameter in the linear regression operator? 
  • olafansau55
    olafansau55 New Altair Community Member
    this is the linear regression hyperparameter that I want to optimize, it is true? or maybe just 1 hyperparameter that i can optimize?

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