How SHAP value is calculated? It is not hard! (simple example)

แชร์
ฝัง
  • เผยแพร่เมื่อ 2 ม.ค. 2025

ความคิดเห็น • 29

  • @DataScienceGarage
    @DataScienceGarage  2 ปีที่แล้ว +4

    Thank you for watching this video. I really appreciate it.
    If you liked this explaining video, I also recommend to check it out other similar videos from my channel below:
    1. Compare ML Models in few clicks with PyCaret in Python - th-cam.com/video/s38AvnzwKPw/w-d-xo.html
    2. Kubernetes Explained | High Level Explanation - th-cam.com/video/7yytUBC8grw/w-d-xo.html
    3. Calculate TF-IDF in NLP (Simple Example) - th-cam.com/video/vZAXpvHhQow/w-d-xo.html
    4. How Gradient Descent Works. Simple Explanation - th-cam.com/video/Gbz8RljxIHo/w-d-xo.html

  • @AJMJstudios
    @AJMJstudios ปีที่แล้ว +3

    Good example. I would suggest though making the distinction between Shapley values and the SHAP calculation more clear, the title is a little misleading.

  • @smithanair787
    @smithanair787 ปีที่แล้ว +2

    Great explanation! Never understood this clearly from other sources!! Well done!

    • @smithanair787
      @smithanair787 ปีที่แล้ว

      If in another video, if you can show how this translates to the mathematical equation for Shapley values, it will be awesome!

    • @DataScienceGarage
      @DataScienceGarage  ปีที่แล้ว

      Thanks for feedback, I really appreciate that you found that useful! :)

    • @DataScienceGarage
      @DataScienceGarage  ปีที่แล้ว

      About - translate to the math. equation - good idea. I will read more about that. :)

  • @encryptionalgorithm
    @encryptionalgorithm 2 ปีที่แล้ว +3

    Thanks for the explanation, I have a quick remark w.r.t. the calculation done at 00:11:03
    MC1 ==> OK
    MC2 / MC3 and MC4 the labels (definition) and the calculations do not align.

  • @senumamit
    @senumamit ปีที่แล้ว +1

    Clear and precise explanation! Thank you so much! Loved it!

    • @DataScienceGarage
      @DataScienceGarage  ปีที่แล้ว +1

      You are welcome. Thank you for watching, appreciate!

  • @umarkhan-hu7yt
    @umarkhan-hu7yt 10 หลายเดือนก่อน +1

    I never see such a clear explanation on Shaley values.

    • @DataScienceGarage
      @DataScienceGarage  10 หลายเดือนก่อน

      Thanks for watching! :)

    • @umarkhan-hu7yt
      @umarkhan-hu7yt 10 หลายเดือนก่อน

      @@DataScienceGarage please make more video on models of XAI.

  • @ssrestore
    @ssrestore ปีที่แล้ว

    Very nice video. It would be nice if the weight you have used could be related to the original shap formula involving factorials.

  • @Poom006
    @Poom006 9 หลายเดือนก่อน

    Great explanation ❤

  • @jamalnuman
    @jamalnuman 10 หลายเดือนก่อน

    the is the best of the best. Many thanks for the efforts

  • @MS-ew2ru
    @MS-ew2ru 2 ปีที่แล้ว +1

    Excellent video! That was very helpful, thank you!

    • @DataScienceGarage
      @DataScienceGarage  2 ปีที่แล้ว

      Thanks a lot for feedback! Happy you like it :)

  • @mohamedezzat5048
    @mohamedezzat5048 2 ปีที่แล้ว

    Excellent explanation

  • @himanshubeniwal
    @himanshubeniwal ปีที่แล้ว

    Thanks for the informative video!

  • @edmar_santos
    @edmar_santos 2 ปีที่แล้ว

    Thanks a lot! This explanation was very helpful!

    • @DataScienceGarage
      @DataScienceGarage  2 ปีที่แล้ว

      Really glad it was useful, appreciate your feedback! :)

  • @Nusa-t2b
    @Nusa-t2b 9 หลายเดือนก่อน

    Thank you so much

  • @utsabshrestha673
    @utsabshrestha673 2 ปีที่แล้ว

    Well explained!

  • @thomaskuttyreji2845
    @thomaskuttyreji2845 2 ปีที่แล้ว

    Thanks a lot

  • @tagheuer001
    @tagheuer001 ปีที่แล้ว +1

    One suggestion, since you pronounce v as w, it's a good idea to just pronounce v's as f's. "falues" is much better than "walues" f an v are so close anyway and I heard you say may f-words clearly.