Implement Support Vector Machine as a Classifier and Regressor

[TarunTomar122]

Related Resource one can follow :-

https://towardsdatascience.com/svm-implementation-from-scratch-python-2db2fc52e5c2
https://www.python-engineer.com/courses/mlfromscratch/07_svm/
https://pythonprogramming.net/svm-in-python-machine-learning-tutorial/
https://fordcombs.medium.com/svm-from-scratch-step-by-step-in-python-f1e2d5b9c5be
http://madhugnadig.com/articles/machine-learning/2017/07/29/implementing-svm-support-vector-machines-from-scratch-in-python.html

[samarth-1729]

I would like to this!

[TarunTomar122]

@samarth-1729 alright Samarth take your time this issue is yours. We will add hacktoberfest tag also. Cheers!

[samarth-1729]

Thanks!

[rohansingh9001]

@samarth-1729 Any updates on this?

[samarth-1729]

I'll start today

[spursbyte]

I can help with this.Can i get the permission?

[rohansingh9001]

@spursbyte It has already been taken and a PR is submitted.

[kwanit1142]

This Issue is now again open for solution.

[iamayushanand]

I would like to contribute to this.

Note: The resource link attached in the statement of this issue has an incorrect implementation of the SVM. Merely changing the input features from X to [X 1] biases the separating hyperplane . (Refer to last paragraph on page 2 here mit 6.867) .

[kwanit1142]

@iamayushanand and @devyani-code, yaa sure u both can contribute to this problem statement.

Regarding the references scenario, you guys can also seek the better ones if necessary :-)

One Advice :- Keep the optionality for the User to pick and choose between variants of SVM Kernels