How to Read & Make Graphical Models?

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  • Опубликовано: 9 сен 2024

Комментарии • 17

  • @tarunbhatia8652
    @tarunbhatia8652 2 года назад +4

    I would say, please keep making videos, you dont know but it helps a lot of people

    • @KapilSachdeva
      @KapilSachdeva  2 года назад +1

      🙏 Thanks Tarun!

    • @bbrother92
      @bbrother92 4 месяца назад

      @@KapilSachdeva Kapil could you explain why we need this?

  • @squarehead6c1
    @squarehead6c1 6 месяцев назад +1

    Great presentation, thanks!

    • @KapilSachdeva
      @KapilSachdeva  6 месяцев назад

      🙏

    • @squarehead6c1
      @squarehead6c1 6 месяцев назад

      @@KapilSachdeva I am reviewing a paper that employs plate models. Had to learn about it quick. :-)

  • @salonikothari7494
    @salonikothari7494 10 месяцев назад +1

    thank you so much Sir.. please sharing - such simple and yet intuitve understanding , especially for complicated concepts... :)

  • @YT-yt-yt-3
    @YT-yt-yt-3 28 дней назад

    What is t1,t2..tn.. are these different instance of target variable? If so why each has different distribution. Are you assuming these categorical target variable and each has it own distribution? This part is confusing me in all the videos.

  • @aarjavik123
    @aarjavik123 3 года назад +1

    Good video thanks

  • @nastaranmarzban1419
    @nastaranmarzban1419 2 года назад

    Hi, hope you're doing well
    I have a question
    Are graphical models the same as multivariate dataset?
    I'm a bit confused🤔
    What's the difference between these two?
    I'll be very thankful if you answer me.
    Thanks in advance🌺

    • @KapilSachdeva
      @KapilSachdeva  2 года назад

      Hello Nastaran,
      The word multivariate simply means that there are more than one (dependent) variables involved in your modeling/experiment. These variables may be independent of each other and/or may be correlated.
      Graphical model term when used in the context of probabilistic modeling primarily specifies how one variable depends (conditions) on another variable(s). Because the primary purpose of the graphs will be specification of conditioning, mostly your graphical models will deal with a multivariate dataset.
      Now graphical models are not the only way to deal with multivariate dataset. You could use many other ML techniques to do so.
      Hope this makes sense.

    • @nastaranmarzban1419
      @nastaranmarzban1419 2 года назад +1

      @@KapilSachdeva thanks a lot
      Your explanations are very clear, I got the answer of my question.
      🌺🌺🙏🙏🌸🌸

    • @KapilSachdeva
      @KapilSachdeva  2 года назад

      @@nastaranmarzban1419 🙏

    • @nastaranmarzban1419
      @nastaranmarzban1419 2 года назад

      @@KapilSachdeva Hi, hope you're doing well.
      Sorry I have a question.
      Is there any multivariate dataset in the internet that the variables are labeled?!!!!!
      As far as I've checked the multivariate dataset that I've seen, are labeled based on observations( for example observation 1 suffer from cancer, 2 do not and....)
      Now I want the variables have lables.
      Is there any data set?
      I'll be bery thankfull if you help me as always.
      Thanks in advance🌸

    • @KapilSachdeva
      @KapilSachdeva  2 года назад

      I think what you are asking for is "multi-labeled" dataset and not necessarily multivariate. A multi-labeled dataset could still be multivariate.
      See if this describes what you are after - en.wikipedia.org/wiki/Multi-label_classification
      For educational purposes, you can build yourself a toy multilabel dataset using scikit-learn
      scikit-learn.org/stable/modules/generated/sklearn.datasets.make_multilabel_classification.html
      I found one page with list of various multi-label datasets but I have never used them.
      www.uco.es/kdis/mllresources/