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https://towardsdatascience.com/support-vector-machines-svm-c9ef22815589
Oct 20, 2018 · Support vector machines so called as SVM is a supervised learning algorithm which can be used for classification and regression problems as support vector classification (SVC) and support vector regression (SVR). It is used for smaller dataset as it takes too long to process.
https://asmquantmacro.com/2016/06/14/support-vector-machines-without-tears-part-1/
Jun 14, 2016 · I have been on a machine learning MOOCS binge in the last year. I must say some are really amazing. The one weakness so far is the treatment of support vector machines (SVM). It’s a shame really since other popular classification algorithms are covered. I should mention that there are two exceptions, Andrew Ng’s Machine…
https://people.eecs.berkeley.edu/~jrs/189/lec/04.pdf
18 Jonathan Richard Shewchuk 4 Soft-Margin Support Vector Machines; Features SOFT-MARGIN SUPPORT VECTOR MACHINES (SVMs) Solves 2 problems: – Hard-margin SVMs fail if data not linearly separable.
https://www.cs.umd.edu/~samir/498/SVM.pdf
Hard Margin v.s. Soft Margin The classifier is a separating hyperplane. Most “important” training points are support vectors; they define the hyperplane. Quadratic optimization algorithms can identify which training points x i are support vectors with non-zero Lagrangian multipliers. Both in the dual formulation of the problem and in the solution
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