Support Vector Machine, Kernel Trick, Svm, Soft Margin Svm, Kernel.
xj) is the kernel function that computes the similarity between two samples xi and xj. It allows SVM to handle nonlinear classification problems by implicitly mapping the samples into a higher-dimensional feature space. The term ∑αi represents the sum of all Lagrange multipliers. Here, W is called