Support Vector Machine, Svm, Svm Algorithm, Svm Classifier, Machine Learning.
Kernel: K(x, x’) = (γx ⋅ x’ + r)^d Captures non-linear patterns by raising the dot product of feature vectors to a specified degree (d), with an optional constant term (r) and scaling factor (γ). 3. Radial Basis Function (RBF) Kernel: K(x, x’) = exp(-γ ||x — x’||²) Measures similarity based on the