Explainable AI using SHAP | Explainable AI for deep learning | Explainable AI for machine learning

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  • Опубліковано 5 вер 2024
  • Explainable AI using SHAP | Explainable AI for deep learning | Explainable AI for machine learning
    #ai #unfolddatascience #datascience
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КОМЕНТАРІ • 7

  • @ryu_no_kagizume
    @ryu_no_kagizume 2 місяці тому

    Could you please let us know how the base value is calculated?
    Thanks!

  • @user-ng4pp7fp6t
    @user-ng4pp7fp6t 2 місяці тому +1

    Hi Aman. Can you pls show, the data in this model. y = x1+x2+x3...+xn. ie. 1000 = 300+250+250+...+150+50, some thing like that.pls

  • @KumRchitect
    @KumRchitect 2 місяці тому

    Hi Aman... It was good to know about this library. But I still have the question about which you touched a little. When we can get weights to see the coef and bias, how does this make it different ?

    • @KumRchitect
      @KumRchitect 2 місяці тому

      I am bit unclear on that. Pl help

    • @UnfoldDataScience
      @UnfoldDataScience  2 місяці тому

      Lets say my prediction for first records is 20000. I want to know what makes it 20000. Can you tell me 14000 of this 20000 is made of feature1, another 2000 from column 2 and another 2000 from feature 3 using coef anf bias?

  • @gadisahayilu5689
    @gadisahayilu5689 2 місяці тому +1

    how to minimize its computation time

    • @UnfoldDataScience
      @UnfoldDataScience  2 місяці тому +1

      It is not slow always - I tried in VS code and local jupyter as well. I was not very dissapointed.