Support Vector Machine, Support Vector Classifier, Kernel Trick, Rbf, Polynomial.
https://www.analyticsvidhya.com/blog/2021/06/support-vector-machine-better-understanding/ The parameters are the distance & γ. If Euclidean distance between X1 & X2 tends to zero, K will be close to 1 . γ is inversely proportional to σ. If σ increases, the region of similarity increases. That means