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What is Understanding Support Vector Machines about?

Support vector machines (SVM) are a type of supervised machine learning algorithm used for classification and regression analysis. SVMs find the optimal separating hyperplane that maximizes the margin between different classes of data points. They can perform both linear and non-linear classification by implicitly mapping input vectors into high-dimensional feature spaces. For non-linear classification, the input is first mapped to a high-dimensional feature space using kernel functions, then a maximal sepa

Author

Aarshena

Language

EN