Support Vector Machine - How Support Vector Machine Works | SVM In Machine Learning | Simplilearn

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This Support Vector Machine (SVM) tutorial video will help you understand the basics of the Support Vector Machine algorithm, where and when to use the SVM algorithm, and how Support Vector Machine works. You will learn about hyperplanes and support vectors, how distance margin helps in optimizing the hyperplane, kernel functions in SVM for data transformation and advantages of the SVM algorithm.
Below topics are explained in this Support Vector Machine Tutorial:
00:00 - 01:03 Applications and Agenda
01:04 - 01:58 What is Machine Learning?
01:58 - 03:39 Why support vector machine?
03:39 - 07:59 What is a support vector machine?
07:59 - 09:15 Advantages of support vector machine
09:15 - 26:42 Use Case in Python
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#SupportVectorMachine #SVMMachineLearning #SupportVectorMachineInMachineLearning #SVM #SVMAlgorithmInMachineLearning #SupportVectorMachines #SVMAlgorithm #MachineLearningTutorial #MachineLearning #Simplilearn
What is a Support Vector Machine?
Support Vector Machines are powerful supervised learning algorithms for both classification and regression. It is a discriminative classifier that is formally defined by a separating hyperplane. So given labelled training data, the algorithm outputs an optimal hyperplane that categorizes new examples.
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Опубликовано:

30 июл 2024

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Комментарии : 292

@SimplilearnOfficial 6 месяцев назад

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@rummi5909 6 лет назад

The slides are impressive and explanation is simple. That was the best tutorial i have seen on SVM

@SimplilearnOfficial 6 лет назад

WooHoo! We are so happy you love our videos. Please do keep checking back in. We put up new videos every week on all your favourite topics. Whenever you have the time, you must also check out our blog page @simplilearn.com and tell us what you think. Have a good day!

@parastooveisi 4 года назад

I've been looking for these easy to understand explanations for a week. Thanks a lot for this great video!

@SimplilearnOfficial 4 года назад

Glad it was helpful!

@bloom6874 Год назад

The best video ever on SVM: learning with fun. You got a great sense of humour and loved your examples 😍😍

@SimplilearnOfficial Год назад

Wow, thank you!

@subtlethingsinlife 3 года назад

Those having problems in application of generating sample blobs, here is the correct syntax and code: import numpy as np import matplotlib.pyplot as plt from sklearn import svm from sklearn.datasets import make_blobs X, y = make_blobs(n_samples=40, centers=2, random_state=20) clf = svm.SVC(kernel='linear' , C=1) clf.fit(X,y) plt.scatter(X[:,0], X[:,1], c=y, s=30, cmap=plt.cm.Paired) plt.show()

@cheggmi3637 3 года назад

I am listening to this again and i must say that even my 5 year old will understand this. You make learning fun. Thank you.

@SimplilearnOfficial 3 года назад

We are so grateful for your kind words. Also, subscribe to our channel and stay tuned for more videos. Cheers!

@arunkumarsamala 2 года назад

Why the splitting of data line is taken cross ??. Can we take the splitting of data line parallel to the y axis

@explorewithjoanne4801 4 года назад

I really like the intro part, very clear and easy to understand especially for someone barely has knowledge in machine learning... I'd really appreciate a lot if you can kindly help me with my question. I want to run nonlinear multiple regression based on 1 dependent variable (engagement rate) and 12 independent variables (color of the picture) all measured at continuous level... I wanted to use SVM but now it seems like it only applies if my data has only two classes. Any suggestion from you? Thank you!

@sharmiislam7015 3 года назад

This slide is well informed and nice to have an hands on example in it.

@SimplilearnOfficial 3 года назад

Thank you for the appreciation. You can check our videos related to various technologies and subscribe to our channel to stay updated with all the trending technologies.

@priyanksisodia5889 4 года назад

i fall in love with your presentations in all videos

@SimplilearnOfficial 3 года назад

Thank you so much 😀

@voticiano 2 года назад

Why in the first code example C=1 and the second example C=1000? what is the difference?

@rahulahoop1 4 года назад

great tutorial! Simple and well explained. Not sure if this has been uploaded but here is the jupyter script:). Although liked typing it out as I'm new to this. import numpy as np import matplotlib.pyplot as plt from sklearn import svm from sklearn.datasets.samples_generator import make_blobs # we create 40 seperable points X, y = make_blobs(n_samples=40, centers=2, random_state=20) # fit the model, don't regularize for illustration purposes clf = svm.SVC(kernel="linear", C=1) clf.fit(X,y) # display the data in graph from plt.scatter(X[:,0], X[:,1], c=y, s=30, cmap=plt.cm.Paired) plt.show()

@SimplilearnOfficial 4 года назад

Glad you enjoyed our video! We have a ton more videos like this on our channel. We hope you will join our community!

@ms.mousoomibora9526 4 года назад

Hi !! Nice explanation about SVM. Looking forward to hear more use cases.

@SimplilearnOfficial 4 года назад

Hey Mousoomi, thank you for watching our video. We are glad that you liked our video. Do subscribe and stay connected with us. Cheers :)

@indrapatel7988 3 года назад

Omg these videos are much better then paid courses. Simply superb and thank you sir,

@SimplilearnOfficial 3 года назад

WooHoo! We are so happy you love our videos. Please do keep checking back in. We put up new videos every week on all your favorite topics. Whenever you have the time, you must also check out our blog page @simplilearn.com and tell us what you think. Have a good day!

@mruduladdipalli5417 5 лет назад

First 4 minutes , it cleared all my doubts Thanks alot

@SimplilearnOfficial 5 лет назад

Hey Mrudul, thank you for appreciating our work. We are glad to have helped. Do check out our other tutorial videos and subscribe to us to stay connected. Cheers :)

@hafzatinnurlatifa2589 3 года назад

The explanation is really understandable, thank youu

@SimplilearnOfficial 3 года назад

You are welcome!

@reddaiahbn9154 5 лет назад

Hi.. I have the following doubts for SVM:I believe both C and Gamma parameters does same job as : trade of between misclassification and boundary surface.in this case why do we need C and Gamma ? Either one will suffice ?Thanks in advance....!

@rulaniya 5 лет назад

Simple and yet to the point... Awesome...

@SimplilearnOfficial 5 лет назад

Greetings! Thank you for your kind words. Spread the word by liking, sharing and subscribing to our channel! Cheers :)

@drpatrickstacey7203 4 года назад

excellent! thanks. note, to do the scatter for 3.6+: import matplotlib.pyplot as plt

@SimplilearnOfficial 4 года назад

Excellent! Thanks for watching out video and sharing your input. Cheers!

@robindong3802 3 года назад

Very impressive and clear SVM video.

@SimplilearnOfficial 3 года назад

Glad it was helpful!

@Blawcky 2 года назад

Honestly I've looked at so many videos on SVM on trying to just understand it and its math, but somehow you've kept it super simple and made me understand it so simply in comparison to all other sources I've seen so far. Thanks so much!

@SimplilearnOfficial 2 года назад

Glad it helped!

@11hamma 4 года назад

Your slides are always awesome

@SimplilearnOfficial 3 года назад

Glad you like them!

@KrishnoSarkar Год назад

Good and easy to understand tutorial on SVM. I would also like to see the math behind separating the data. Is SVM separates data into two sets only?

@SimplilearnOfficial Год назад

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@anandiborade6349 3 года назад

love your tutorials!!

@SimplilearnOfficial 3 года назад

Glad you like them!

@samratsengupta8881 4 года назад

My goodness! is it that simple? Are you serious? I have learnt what 2 days of online R&D did not do for me. I have no doubt that i am at the right place now.............god bless this team SUBSCRIBED!!!!!!!!

@SimplilearnOfficial 4 года назад

@ahmadrezasy4874 5 лет назад

Simple and great demo of SVM. I learned a lot. I didn't clearly understand the last part of the code. How did he actually found the hyperplane and the two support vectors (dashed lines) using contour function? I googled the contour and understood how it works but I couldn't figure it out in this part.

@SimplilearnOfficial 5 лет назад

Hi Ahmad, thanks for bringing your query to us. The Hyperplane and support vectors are found based on the kernel function.

@mariav1234 4 года назад

Very nice tutorial. Thanks.

@SimplilearnOfficial 4 года назад

You are welcome!

@inquisitivelearner8649 Год назад

So, is this one of the classification algorithms?

@petyaslavkova3405 3 года назад

the whole playlist is masterpiece

@SimplilearnOfficial 3 года назад

Thanks for watching our video and sharing your thoughts. Do subscribe to our channel and stay tuned for more. Cheers!

@ujjwolpandit1046 5 лет назад

You just did an amazing job. I have been try to use this algorithm for detection of diabetic retinopathy. And, there are four stages images need to be recognized in their distinguished stage. Can you please help me out? thank you :)

@SimplilearnOfficial 5 лет назад

Please elaborate your question so that we can help you with a relevant answer. Thanks.

@kevindeng3576 5 лет назад

I don't really understand the line 15 at 23:05. What does the decision function do? Does it give the hyperplane we are looking for? Also, I think the "reshape" is just to make the Z the same dimension of XX and YY, in order to use the contour function. Could someone explain the decision function part for me?

@SimplilearnOfficial 5 лет назад

The decision function is completely indicated by a subset of preparing tests. and yes, the reshape is used to give a new shape to an array without changing its existing data. Hope this helps!

@lakshyabhardwaj9541 3 года назад

Create a video with more deeper concepts of SVM. (for eg:- how kernel works) and stuff like that. this was a very nice video.

@SimplilearnOfficial 3 года назад

Hey Lakshya, thank you for watching our video. We will definitely look into your suggestions. Do subscribe and stay tuned for updates on our channel. Cheers :)

@Vinay1272 4 года назад

Hey, I couldn't get that contour plot as the output in the end. I didn't get any output at all. I have rechecked the code over but unable to figure it out. What possibly could be the reason?

@SimplilearnOfficial 4 года назад

HI Vinay, could you please elaborate your issue or show the code in the comment section. Thanks.

@rayuduyarlagadda3473 6 лет назад

Nice explanation team simplilearn. I have few doubts I hope u will clear 1.what is alfa and how to select best k value in case if my data is not linearly separable. 2.what is the difference b/w logistic regression and SVM? 3.relationship b/w k in k-nn and sigma in the rbf kernel.? I got this doubt when I am referring about kernels....

@SimplilearnOfficial 5 лет назад

Hi Raydu, thanks for watching our tutorial. Here are the answers to your questions below. no.1 what is alpha? In SVM, Alpha % is a vector of weights where the positive % weights are the support vectors. If the data is not linear-separable, a kernel function should be used no. 2 Logistic regression: Logistic regression is used to predict the dependent variables (i.e.,) the dependent variable can take only two possible values such as “Yes or No. SVM: Support Vector Machine is a frontier which best segregates the two classes (hyper-plane/ line). SVM selects the hyperplane which classifies the classes accurately prior to maximizing margin(support vector line) no. 3 'K' in K-NN means the number of clusters the algorithm is trying to identify from the data. Sigma: Sigma is a parameter you may choose the value to change how the SVM trains.

@nilesh946 5 лет назад

The presentation was very good. What software/package was used to make it?

@SimplilearnOfficial 5 лет назад

Hi Ravi, thanks for appreciating our work. We use MS Powerpoint and Adobe to make such presentations. Hope that helps!

@ayoubmarah4063 4 года назад

it takes 15 min for the model to fit the data with svm and 2 hours to do 10 fold cross validation its so slow

@tokeyahmmed 4 года назад

Superb explanation

@SimplilearnOfficial 4 года назад

Hey Tokey, thank you for watching our video. We are glad that you liked our video. Do subscribe and stay connected with us. Cheers :)

@qaiserhussain1861 6 лет назад

Based on the hyper plane ,we can say the new data point belong to male .. I didn't get it ! How can u say this like on what figures or equation u said this ... ? plz explain !

@SimplilearnOfficial 6 лет назад

Hi Qaiser, Thank you for watching our video. In SVM, support vectors are drawn on both the sides of hyperplane at an equal distance. Whenever we add a new point, we check the distance of the new data point with the support vectors of both the classes. Based on the shortest distance to the support vector, we will assign the new data point to that class. If you still have any persisting doubts regarding SVM, kindly post it in the comment section. Also, do subscribe and hit the bell icon for not missing another update.

@jsx0328 6 лет назад

What does line 14 mean? np.vstack([XX.ravel()... Kinda confused at this point.

@SimplilearnOfficial 6 лет назад

Line 14 takes a sequence of arrays and stacks them vertically to make them into a single array.

@hajaraltam3505 3 года назад

amazing presensation full of informations , please can u share with us the slides

@SimplilearnOfficial 3 года назад

Hello, thanks for viewing our tutorial. It would be helpful if you will provide your email ID to us so that we can send the requested dataset promptly. On the off chance that you need your email ID to be kept hidden from others, we can do that too. Hope that helps.

@kielquitain1907 5 лет назад

How to apply svm for sentiment analysis?

@SimplilearnOfficial 5 лет назад

Hi Kiel, the question you have asked is very hard to describe in the comment section. Do check this link for knowing more about sentiment analysis: www.researchgate.net/publication/286583940_Sentiment_analysis_using_Support_Vector_Machine

@anshulkumarprajapati8346 2 года назад

Amazing

@SimplilearnOfficial 2 года назад

Thank you! Cheers!

@Harsh-pf4mq 5 лет назад

It was really great watching these informative slides but can you please tell how could this algorithm be used in image classification won't some other method like logistic regressiion or naive bayes give us more intutive answer for such a problem.

@SimplilearnOfficial 5 лет назад

Hi, it is very difficult to explain the answer in the comment section. So we are giving a blog link where you find the answer to the above question: medium.com/@dataturks/understanding-svms-for-image-classification-cf4f01232700.

@riteshpatidar9184 5 лет назад

You can use image pixel values as inputs(or features)....Convolution Neural Networks will work better(more than better)

@SimplilearnOfficial 5 лет назад

Hi Patidar, thanks for your input. Thanks!

@sofiakampioti1439 4 года назад

Great video! I would like the source code , if possible!

@SimplilearnOfficial 4 года назад

Hello Sofia, thanks for viewing our tutorial. It would be helpful if you will provide your email ID to us so that we could send the requested dataset promptly. On the off chance that you need your email ID to be kept hidden from others, we can do that also. Hope that helps.

@faisalrauf8936 2 года назад

SIR , your explanation is too good ..can you share the above code of python

@SimplilearnOfficial 2 года назад

Hello, thanks for viewing our tutorial. You can find your requested dataset in the video description. Hope that helps.

@aishasiddiquadabeer5143 4 года назад

Thank you Simplilearn team for the clear explanation. Can you please provide the dataset and the python notebook used in the video?

@SimplilearnOfficial 4 года назад

Hi Aisha, we are glad you found our tutorial informative. It would be helpful if you will provide your email ID to us so that we could send the requested dataset promptly.

@namangupta3767 5 лет назад

What if a data is misclassified into another class, how will we then train the machine to ignore that and create the original decision boundary?

@SimplilearnOfficial 5 лет назад

If there's a misclassification in another class then there decision boundary will not be accurate. SVM is trained in a way where it classifies classes based on the input data.

@VarunSharma-xc9fl 2 года назад

My college teacher studies and teaches from your channel only.

@SimplilearnOfficial 2 года назад

Keep learning with us .Stay connected with our channel and team :) . Do subscribe the channel for more updates : )

@wowovanmbothen 4 года назад

what if we have 3 classes? what should i do to find the right class?

@SimplilearnOfficial 4 года назад

Hi, thanks for watching our video. We have sent the requested dataset to your mail ID. Do show your love by subscribing to our channel using this link: ru-vid.com and don't forget to hit the like button as well. Cheers!

@kasis7693 5 лет назад

How to classify 3 or more classes using svm??

@SimplilearnOfficial 5 лет назад

Hi, thanks for watching our video. Suppose your training dataset contains more than two classes, SVM automatically handles multi-class prediction. Hope that helps!

@marivallithaip9076 4 года назад

good sir. Can you please share the 1000_Companies csv?

@SimplilearnOfficial 4 года назад

Hello Marivallithai, thanks for viewing our tutorial. It would be helpful if you will provide your email ID to us so that we could send the requested dataset promptly. On the off chance that you need your email ID to be kept hidden from others, we can do that also. Hope that helps.

@kasis7693 5 лет назад

How to implement multiple svm?? Same as svm

@SimplilearnOfficial 5 лет назад

Hi, thanks for watching our video. Multiclass SVM can be implemented by combining several binary SVMs. Cheers!

@chiradeepdeb745 5 лет назад

what does gca do?

@SimplilearnOfficial 5 лет назад

GCA gives a response of the "handle" of the axes object.

@TheSantu1985 3 года назад

Why no video of simplilearn have mathematics behind the algorithm...

@SimplilearnOfficial 3 года назад

For that you can take up our course as it will give you an in-depth understanding of the maths

@clarence6839 5 лет назад

can SVM be used to classify data into 3 or more types? thanks

@SimplilearnOfficial 5 лет назад

Hi Clarence, thanks for watching our video. Support vector machines were originally designed to solve only two-class-problems but it can be used for multiclass problems also. Hope that helps!

@tracyding4906 5 лет назад

Can you give us the source code thru github? or some downloadable link?

@SimplilearnOfficial 5 лет назад

Hi Tracy, We have already sent the requested source code to your mail ID. To subscribe to our channel and get our new video updates directly into your email. If you have any questions related to these videos, you can post in the comments section, we will clear your queries/doubts.

@mahdiislam869 3 года назад

Can I please get the dataset

@SimplilearnOfficial 3 года назад

@mahdiislam869 3 года назад

@@SimplilearnOfficial I want to keep my email hidden.

@mahdiislam869 3 года назад

@@SimplilearnOfficial I want to keep my email hidden.

@ostheperson 4 года назад

The recent gender changes would make the gender classifier invalid :>

@ostheperson 4 года назад

Unless, it is possible to make a gender classifier that can identify transgenders, non-binary e.t.c. :)

@vidhyareddy61 4 года назад

can u pls send me the data set used

@SimplilearnOfficial 4 года назад

Sure. It would be helpful if you will provide your email ID to us so that we could send the requested dataset promptly. On the off chance that you need your email ID to be kept hidden from others, we can do that also. Hope that helps.

@mr.bilalabdualgalil4559 3 года назад

Plz share this code

@SimplilearnOfficial 3 года назад

Hello Bilal, thanks for viewing our tutorial. It would be helpful if you will provide your email ID to us so that we could send the requested dataset promptly. On the off chance that you need your email ID to be kept hidden from others, we can do that also. Hope that helps.

@SimplilearnOfficial 6 лет назад

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@rasikajain7263 5 лет назад

v good video sir ..can you send the ppt of this video on this mail id rasikakhule1997@gmail.com ...ty in advance..

@SimplilearnOfficial 5 лет назад

Hi Rasika, thanks for watching our video. We have sent the source code for this video to your mail ID. You can get the access to the PPT by clicking this link: www.slideshare.net/Simplilearn/support-vector-machine-how-support-vector-machine-works-svm-in-machine-learning-simplilearn. Also, subscribe to our channel by clicking on the bell icon for never missing another update. Cheers!

@shishirkumar4932 5 лет назад

Hi, nice video. Could you please share the code to my id as well - shishirkumar123@gmail.com.

@SimplilearnOfficial 5 лет назад

Hi Shishir, thanks for watching our video. We have sent the requested source code to your mail ID. Also, subscribe to our channel by clicking on the bell icon for never missing another update. Cheers!

@vaibhavpandey7618 5 лет назад

Hi, thank you for nice video and explanation. Do you have any video or resources for multi-label classification using SVM?

@mr.bilalabdualgalil4559 4 года назад

nice, thanks plz send me dataset and algorithms to this email

@SimplilearnOfficial 4 года назад

@amrelshall293 3 года назад

the code please

@SimplilearnOfficial 3 года назад

Hello Amr, thanks for viewing our tutorial. It would be helpful if you will provide your email ID to us so that we could send the requested dataset promptly. On the off chance that you need your email ID to be kept hidden from others, we can do that also. Hope that helps.

@datasciencecamp 4 года назад

Kindly share the code please

@SimplilearnOfficial 4 года назад

Hello Nikita, thanks for viewing our tutorial. It would be helpful if you will provide your email ID to us so that we could send the requested dataset promptly. On the off chance that you need your email ID to be kept hidden from others, we can do that also. Hope that helps.

@datasciencecamp 4 года назад

@@SimplilearnOfficial nikita.malhotras@gmail.com

@ahmedhassankotb8785 5 лет назад

can you send me the data

@SimplilearnOfficial 5 лет назад

Hello Ahmed, thanks for viewing our tutorial. It would be helpful if you will provide your email ID to us so that we could send the requested dataset promptly. On the off chance that you need your email ID to be kept hidden from others, we can do that also. Hope that helps.