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https://towardsdatascience.com/support-vector-machine-introduction-to-machine-learning-algorithms-934a444fca47
Jun 07, 2018 · Support Vector Machine, abbreviated as SVM can be used for both regression and classification tasks. But, it is widely used in classification objectives. What is Support Vector Machine? The objective of the support vector machine algorithm is to find a hyperplane in an N-dimensional space(N — the number of features) that distinctly classifies ...Author: Rohith Gandhi
https://blog.quantinsti.com/support-vector-machines-introduction/
Support Vector Machines. A Support Vector Machine is an approach, usually used for performing classification tasks, that uses a separating hyperplane in multidimensional space to perform a given task. Technically speaking, in a p dimensional space, a hyperplane is a flat subspace with p-1 dimensions.
https://www.kdnuggets.com/2019/09/friendly-introduction-support-vector-machines.html
Over a period of time, many techniques and methodologies were developed for machine learning tasks. In this article, we are going to learn almost everything about one such supervised machine learning algorithm which can be used for both classification and regression(SVR) i.e. Support Vector Machine …
https://towardsdatascience.com/a-friendly-introduction-to-support-vector-machines-svm-925b68c5a079
Sep 06, 2019 · Introduction. Support Vector Machines(SVM) are among one of the most popular and talked about machine learning algorithms. They were extremely popular around the time they were developed in the 1990s and continue to be the go-to method for a …Author: Nagesh Singh Chauhan
https://towardsdatascience.com/introduction-to-support-vector-machine-svm-4671e2cf3755
Jan 21, 2019 · Support vector machine (SVM) The support vector machine is an extension of the support vector classifier that results from enlarging the feature space using kernels. The kernel approach is simply an efficient computational approach for accommodating a non-linear boundary between classes.Author: Marco Peixeiro
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