Linear Regression Cost Function | Machine Learning | Explained Simply
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- เผยแพร่เมื่อ 30 ก.ย. 2024
- Learn what is Linear Regression Cost Function in Machine Learning and how it is used. Linear Regression Cost function in Machine Learning is "error" representation between actual value and model predictions.
To minimize the error, we need to minimize the Linear Regression Cost Function. Lesser the cost function, better the learning, more accurate will be the predictions.
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Dividing the cost function by 2 is not for finding the average. It is just for convenience when the squared function is differentiated, the nominator gets a 2 for multiplication factor. So to eliminate this we just put a 2 in the denominator, I suppose.
Actually,i m seeing for this in comment's section .thanks :)
@@hjlruk x2
Are u student of prof. Andrew Ng? Your teaching style is very much similar to him. Anyway thank you for a great video.
I learned ML first from him only... and really liked his teaching. Yea... and that is why my teaching style has been adapted to his. Good to know that you found my video helpful.
The 2 exponent is there to eliminate negative numbers and not because of the magnitude of the data points. If anything squaring would make them even larger.
Yes right . Making them larger won’t be a problem, because the graph of cost vs weight will remain the same way, and we will be able to reach to the local minima of that graph.
You can try once by taking absolute value without squaring, and then try again with taking square, you will get the same accuracy and results in both cases.
Hello, JP. You explained it really very well. Thank a lot.
Just have a query... why do we apply square for our cost function. is it really necessary?
Hi Murali, you either need to square the cost function or take modulus of it.
What we want is positive number for the difference between actual value and predicting value.
Otherwise we will not be able know how large is our error.
For eg, if our error differences are 3, -4, 2. Then cost should be = (3 + 4 + 2 )/3 = 3.
If we don’t square or take modulus of these errors then it will mislead us giving the cost function value to be = (3 - 4 + 2 )/3 = 0.33
@@CodingLane thanks a lot for your quick reply. I really understood it in now in very good manner.
I really appreciate your effort for teaching others.
my qn is why the square is taken? modulas was okay but why sq? next, I'm not getting why again 1/2m is needed, 1/m is okay for average but again the 1/2??
Hi Supriya... good question... the answer of this is already given in comments below.
This is my first time accessing such a video and it is a clear way of description, thank you!
Thank you for the appreciation. Glad it helped! 🙂
You got a new sub man, i didn't know this can be this simple, i really appreciate it.
Thank you 😇
It should be y predicted - y actual
Great explanation brother
Thank You Ankit !
You sir should be a professor
I am just a student for now . Thank You so much ! It really means a lot to me ! I am glad my videos helped you.
best explanation on cost function. Thank you for making it so simple!
I think the formula of cost function in this video isn't right
Hi Aaftab, it is correct. There can different cost function formulas, depending on the type of model you are creating.
Can someone please explain why did we multiply by 1/2m?
Hello Maliha, thanks for your question.
As we are taking the sum of squared errors of all m datapoints, dividing it with (1/m) will give us the average. Thus we multiply (1/m) to get the average of squared error.
You can choose to multiple (1/2m) or (1/m), it wont affect our model.
But multiplying (1/2m) makes the expression mathematically simple when we are dealing with squared error.
Hope it helps! Let me know.
@@CodingLane Thank you for the response! I finally get it
@@CodingLane worse language i have ever seen. Bro she asked 2/m. i already know why we multiply with 1/m but why 2? WHY 2 TWO
Good job. Just please stop trying to force an american accent. Doesn't matter what accent you have, you are intelligent enough to explain tought concepts to everyone. Just be you
Thank you so much ! And I am not trying to force my accent, its now natural to me 😅. I am glab that you found my videos helpful.
He is not trying,actually i enjoed his videos though I don’t like to hear indian accent-@the channel onwer u did great
why 2m specifically? There are differences of 2m points, but there are only m values.
cost function can be any function for those who are asking why dividing by 2 . of course the ones that makes sense and we can minimize is a function power of 2 so that's why
I honestly don't get why you squared it, and divided it by 2m. What's the problem in just considering the summation of all distances?
(Y - y_hat) can be negative (when our straight line is above a point), so it will lead to wrong answer if we just sum it. So if you don’t want to square it, then take its modulus i.e, | Y - y_hat | .
And about the 2m, i have already answered that in the comment down below. Do check that out.
@@CodingLane Thanks for the response 😀
ty
Welcome 😇
Explained in such easy to understand language, this was my first video tutorial and I understood it pretty well.
Thank you.
I am very glad to be able to help you! Your comment really means alot to me.. Thanks alot !!
I love it. Greetings from Germany!
Thank You so much! I am really glad you liked it !
Great explanation, but didn't get the point of multiplying with 1/2m in case of squared or 1/m in case of absolute. Thank You
I have explained that in comments section below… you can have a look at it… it might help
I think that theres an error i your cost formula, isnt (y-y^) its (y^-y).
Actually in the implementation withh Python you use this (y^-y)
Hi Francisco, it’s appropriate.
@@CodingLane Please upload more videos with other models...
Are very helpfull
go ahead
Thanks alot Ijaj. This means alot to me !!
nice explanation about the cost funtion bro understood the concept
Thanks alot Shajan! This means much to me. Glad to help !
That's great as I took a premium course from google.... I came here for revision, as I wonder if you could explain it in simpler terms.... Great explanation 👍
Thank you so much!
what is the catch behind fake accent.
Its now kind of natural to me 😅. But i will improve to have more of an Indian accent
Cool video thank U ...when you try to tune for example the PI control Gains (kp, ki) of a closed loop sys by " genetic algorithm " the cost is the same as fitness function ...and if want to suggest to me any thing can help to code this in matlab. Thanks again for the effort
Your hands are pretty 😂
Haha… thanks! Its the most unique compliment I have received 😁
Are you from india.. your english accent is good..
And btw video is nice..
Thank You so much! Yes, I am from India
That is a very much good explanation. thanks for your this help
You’re welcome!
really good explanation! thanks very much. greetings from brazil
Hi Mauricio Jean... Good to see you. Thanks for the compliment.
Nice explanation dude
Thank you! 🙂
Thanks man , that was an excellent explanation^^, keep rocking \m/
Glad it helped!
Why you devide by 2
I have answered this in the comments below
Thanks bro 😜👍
Thank you so much ! Your comments mean something to me.
Very clear explanation. Thank you for the video!
Your welcome
good explanation
Thank you!
thank you :)
You're welcome!
The lesson from my professor(formula without demonstraton) make me sleepy all the time, but u make it look very simple problem and understandable. Thank you!
Glad I could help 😄
Easy to understand this video. Thanks, coding lane.
You’re welcome!
Thanks mate
Your Welcome!
In this example you initiated randomly a curve. But in fact, how can we initiate the first equation/curve/line?
Thank you
Welcome!
Thanks man
Your Welcome
Than you! Very clear explanation, never imagined this would be such easy to understand.
Your welcome!
WOW! Thank you for this.. I had been trying to look everywhere which simplifies the explanation of Mean Squared Error and what its purpose into few minutes and you did superb! Just in time for my research.
Glad I could help!
jz luv the way u gave the intro ..... it's quite easy to learn from ur videos
Thank You so much Jeevapriya ! This really means to me !
excellent
Thank you !
why divide by 2M?
This was such a great explanation! thank you !!!!
thankyou!!
GOod explanation. Thanks!
Thank you !
Thanks man, very good job !
Welcome!
Thanks for explaining in the best possible and easy way. I was finding this very hard but after watching this video I understood it
Thanks ! I am happy that you found value from the video !
great tutorial !
Thanks alot Jason !! Glad to help !!
thanks bro explanation is superb
Your welcome!
Thanks
Zesty
nice
thank you this was perfect
Your Welcome!
This was awesome thank you so much
Glad to help!
This really helped thanks!
Your Welcome!
Thank you man! Keep it up 💪
Sure 🤗
thanks soo so much mate.
Your Welcome !
Great math explanation!
Thanks a lot!
Thank you for this excelent class!
Your Welcome Daniel !
Excellently explained, thanks!
Thank You... I appreciate your comment!
Very well explained. U are amazing 😊
Thank You so much! It's my pleasure to create content
Thank You so much! It's my pleasure to create content
Brief... Explanatory... Great....
Thanks a lot Hemant ! Really appreciate it !
💯
Thank you!
You are a GEM. explaining in simple words with drawing.
Really well explained! Thanks!
Thank You Stephen ! My Pleasure 😇 !!
thank you so much dudee
He is just great
Thank you so much
Thank you.
Your Welcome Farhan !
cool video!!
Thanks Akshay !
great video, thanks
Excellent
Hi, great lecture. Besides your lectures, which book or online course would you recommend to learn ML topics (KNN/SVM etc.) in depth?
did you find a book like that?
Woow nice explanation 👏👌
Thank you
👍👍👍👍👍👍👍
Thanks 😇 !!
you explained better than Andrew ng honestly
Thank you so much ! This really means a lot to me.