SVDD vs once Class SVM

Can some one please explain me what is the difference between one class SVM and SVDD(support vector data description)

• Is there experience around in which cases one of these models is superior? – MaxS Dec 20 '18 at 6:16

If the kernel function has the property that $$k(\mathbf{x}, \mathbf{x}) = 1 \quad \forall \mathbf{x} \in \mathbb{R}^d$$, SVDD and OC-SVM learn identical decision functions. Many common kernels have this property, such as RBF, Laplacian and $$\chi^2$$.