Non Linear Support Vector Machines (Non Linear SVM)

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  • Опубліковано 29 жов 2024

КОМЕНТАРІ • 27

  • @Unwritten48
    @Unwritten48 9 років тому +10

    Hi, how did you decide that the Ф function should be 6-x1.. etc.? And why is the square root in the condition?
    I understand that the points in the blue class lie on the circle x1^2 + x2^2 = 2 since the radius of this circle is the square root of 2. Yet, I can't figure out how did you get the Ф function.

    • @myary0604
      @myary0604 8 років тому +1

      +Unwritten48 have you found it? If you haven't found it try to search more about kernel trick. nlp.stanford.edu/IR-book/html/htmledition/nonlinear-svms-1.html

    • @jugalbhatt7475
      @jugalbhatt7475 7 років тому +1

      Hi Ary. Could explain, with an example elaborating the video explaination on how 6 is found?

  • @dr.harshavardhanawari2776
    @dr.harshavardhanawari2776 5 років тому +2

    sir wonderfull expalnation. can you please take one example of coordinates and how the linear,polynomial and gaussian kernels are working to classify the proble.

  • @gou-goutham
    @gou-goutham 10 років тому +2

    Thank you very much.... It is so helpful.
    simple and clear.

  • @rahulbalan
    @rahulbalan 7 років тому +5

    How did you choose the mapping function? What about Kernel Tricks? What are those and how are they incorporated in this video? This video is good but is so customized is kinda useless to people trying to learn non-linear SVM.

  • @yahiagamal937
    @yahiagamal937 2 роки тому

    Hi sir,
    Thank you for making life easy.
    I have two questions if u don't mind:
    is the formula 6- x1+(x1-x2) greater or equal to 2 fixed? i.e. in our example, the read points make a boundary of max 2. Is that the reason you chose greater or equal to 2 or this is a fixed equation regardless of the coordinates of the points?

  • @victor_ajadi
    @victor_ajadi 2 роки тому

    pls make a video of how you derived the mapping function

  • @anandachetanelikapati6388
    @anandachetanelikapati6388 5 років тому

    Thanks. It eases out the terminology kernel, Lagrangian multiplier, vector algebra, etc. It the procedure appears to be working on trivial cases. I've tried with few points but it doesn't seem to be yielding correct results.

  • @nafassaadat8326
    @nafassaadat8326 3 роки тому

    Thank you Sir. One thing, how to choose the mapping function ???

  • @gursimarkaur9340
    @gursimarkaur9340 6 років тому

    I think once we find the support vectors, we again need to apply the Ф function on it and then use in the equations. Is that the case??

  • @bhawnajain3968
    @bhawnajain3968 7 років тому

    This is really nice.. Very well explained!!

  • @dhruvildalal5899
    @dhruvildalal5899 4 роки тому

    sir why you have taken value 0.0859 during multiplication because actual value is 0.859

  • @yeganehjalali7307
    @yeganehjalali7307 5 років тому +1

    how you define your map function?

  • @keshriverma
    @keshriverma 7 років тому

    Awesome to understand SVM

  • @akino.3192
    @akino.3192 6 років тому

    Great tutorial. Well done!

  • @darshansolanki5535
    @darshansolanki5535 6 років тому

    what does alpha1, alpha2, alpha3 signifies? what is it used for?

  • @RaviShankar-jp8pk
    @RaviShankar-jp8pk 6 років тому

    and please can you show in libsvm how training and testing of data is done and how to fine support vector if there are many data in this we can easily guess the support vector but if data is too big then how do we guess the support vectors

  • @moeezranksol6925
    @moeezranksol6925 2 роки тому

    From where the 6 comes?

  • @RaviShankar-jp8pk
    @RaviShankar-jp8pk 6 років тому +1

    how do we come to know which one are the support vectors if there are so many points in the datasets

    • @newday2061
      @newday2061 6 років тому

      really how? I also ask like your question

  • @MasayoMusic
    @MasayoMusic 8 років тому

    Nice work.

  • @TheMRfaizanpakistani
    @TheMRfaizanpakistani 8 років тому

    Very nice. Thanks!

  • @jnssjanardhananaidu2256
    @jnssjanardhananaidu2256 10 років тому +2

    it good and understanble

  • @TaherAnjary
    @TaherAnjary 4 роки тому

    EXCELLENT!

  • @omerutkuerzengin3061
    @omerutkuerzengin3061 9 років тому

    Thank you.