Solved Support Vector Machine | Linear SVM Example by Mahesh Huddar
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- Опубликовано: 11 сен 2024
- Solved Support Vector Machine | Linear SVM Example by Mahesh Huddar
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Solved Non-Linear SVM Example: • Solved Support Vector ...
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Easy to understand explanation on SVM. This is by far the most simple approach with example. Thank you sir!
Straight to the point man!! I was able to solve a 1-D sample problem applying same concept thanks to this thank you!!
i have an exam in 2 hours, thank you so much for clearing this out for me
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All the very best for your exams
Us bro us my exam is in 1 hour and im here cause i have a crush on this sir he’s voice is so hot omgg face reveal soon sir
How was your exam?
thank you sir i love your video so much clearer than my prof
7:55 but how you solve that
Very well explained .. thanks for creating this video., simply the best video i saw on SVM
awesome video on SVM, and explained very well.
Sir the offset is -2 then how it lies at 2 are we calculating from origin? And if yes then what does "-" Sign has to do with it?
I too have the same question. Please let me know if you get it. Thank you !!
@Mahesh Huddar plz reply this question..i also have same doubt
Same question here.
same question, anyone with a good explanation please
Same Doubt
It's a clear explanation thank you so much
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your videos are very nice... keep uploading..
Thank You
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Sir why do we take bias is 1
Why?
No why
Assume krte h bro
Thanks a lot sir .!!!!!!!!!!!!!! literally tomorrow is my exam and in one shot video you made it clear
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Thank you so much! that was a very clear explanation.
sir thank you for your nice explaination.Here you used only 2 variables..but if there are more than two variables how we can plot that in 2D?......
You cannot since it's multi dimensional plane.. we cannot see and draw it..
very good and easy explanation sir ,you are a great and true teacher ,thanks !!
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OMG thank you so much! Good explanation.
Nice explaination ...thnx
Very Nice Explanation,Sir.Nedds More Tutorial From You.
Thank You
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Thankyou so much !!
It was very helpful :)
Very well explained.
Thank you for a helpful video.
Thank you for making the video.
great explanation sir. thank you
Great explanation 👌
greatest svd vid
can u suggest, which book u have taken this problem
Nice explaination ❤️
The explanation is very useful sir, I kindly requesting you that do you have code for this example sir?
Thank you very much for great explanation
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it was so helpful! thanks.
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sir how did you got offset as -2
Good morning sir, i have a doubt in this question that why we took three points s1,s2,s3 . To calculate alpha1,alpha2,alpha3 .... 'm i thinking right please let me know. N y we choose only those particular point.
because those are the nearest points to each other if there will be five points then u need to calculate s1,s2,s3,s4,s5
أحسنت بارك الله فيك
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sir is it necessary that we will always have to choose 3 support vectors?
amazing video thanks
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Nice one sir
Sir, kindly take classes for all ml algorithm numerically and try the same example in jupyter notebook.
It's really good one. Got an insight how this works. Thanks
thank u so much sir....
Most welcome
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Good one ..
Sir how do we get this form, 3:47th minute in the video.
Grt sir
Super excellent explanation sir
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more than wonderful
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Hi Mahesh, could you please make a video on SVR with a solved example.
sir any book you use in machine learning pls help
You're God bro
7:06 i didn't understand how did you got the value of alpha1,2 & 3
Solve using substitution (use substitution to reduce number of unknowns in equations, until you can solve):
START WITH FIRST EQUATION (get a_1 on its own):
2a_1 + 4a_2 + 4a_3 = -1
2a_1 = -1 - 4a_2 - 4a_3
a_1 = -0.5 - 2a_2 - 2a_3 (EQUATION 1.1)
SUB 1.1 INTO SECOND EQUATION:
4a_1 + 11a_2 + 9a_3 = 1
4 * (a_1) + 11a_2 + 9a_3 = 1
4 * (-0.5 - 2a_2 - 2a_3) + 11a_2 + 9a_3 = 1
-2 - 8a_2 - 8a_3 + 11a_2 + 9a_3 = 1
-2 - 8a_2 + 11a_2 - 8a_3 + 9a_3 = 1
-2 + 3a_2 + a_3 = 1
GET a_2 ON ITS OWN:
3a_2 = 3 - a_3
a_2 = 1 - 1/3 * (a_3) (EQUATION 2.1)
SUB IN 1.1 AND 2.1 INTO THIRD EQUATION:
4a_1 + 9a_2 + 11a_3 = 1
4 * (a_1) + 9 * (a_2) + 11a_3 = 1
4 * (-0.5 - 2a_2 - 2a_3) + 9 * (1 - 1/3 * (a_3)) + 11a_3 = 1
-2 - 8a_2 - 8a_3 + 9 - 3a_3 + 11a_3 = 1
7 - 8a_2 - 11a_3 + 11a_3 = 1
-8a_2 = -6
8a_2 = 6
a_2 = 0.75
NOW WE HAVE a_2, SUB a_2 INTO 2.1:
(a_2) = 1 - 1/3 * (a_3)
0.75 = 1 - 1/3 * (a_3)
-0.25 = -1/3 * (a_3)
0.25 = 1/3 * (a_3)
0.75 = a_3
NOW SUB a_2 AND a_3 INTO 1.1:
a_1 = -0.5 - 2(a_2 ) - 2(a_3)
a_1 = -0.5 - 2(0.75) - 2(0.75)
a_1 = -0.5 - 1.5 - 1.5
a_1 = -0.5 - 3
a_1 = -3.5
SO,
a_1 = -3.5
a_2 = 0.75
a_3 = 0.75
Also, solving by substitution will only work when the number of equations are equal to or greater than number of unknowns.
@@joshuac9142 where did the initial equations come from? how did we get these equations to plug numbers into? thank you.
@@shivanishah7275 They are the equations he gets at 6:42
How the Hyperplane Had been taken in the Above example Without any Explanation ? @mahesh Huddar Sir
Cool
Thank You
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how to decide these are my support vector points
Sir values of alpha 1,2,3 are coming different
How did you get the three equations at 3:40
can you let me know , if you know how he got three equations
sir, video 55 and video 54 are same.
Ok
I will check
based
Based...?
pass thai gaya toh tnne party aapise
sir how to calculate w~?
[{(-3.5 * 1) + (0.75 * 3) + (0.75 * 3)}, {(-3.5 * 0) + (0.75 * 1) + (-1 * 0.75)}, {(-3.5 * 1) + (0.75 * 1) + (0.75 * 1)}] Hope you got this.
Edi machine learning Kuda na
OPA OPA
Means..?
Great explanation sir. Thankyou so much 🙏🏻
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Nice one sir