An approach to the Gaussian RBF kernels via Fock spaces

We use methods from the Fock space and Segal–Bargmann theories to prove several results on Gaussian RBF kernel in complex analysis. The latter is one of most used kernels modern machine learning support vector classification algorithms. Complex analysis techniques allow us consider notions linked radial basis function (RBF) kernels, such as feature map, using so-called transform. also show how can be related some operators quantum mechanics time frequency analysis; specifically, we connections with creation, annihilation, Fourier, translation, modulation, Weyl operators. For operators, study a semigroup property this case.