Classification, Support Vector Machine, Roc Curve, Rbf Kernels.
be linearly separable at all, that is, the class boundary is not linear. In that case, we can project the feature space in higher dimensional space, so that a nonlinear boundary in the feature space becomes a linear boundary in the higher dimensional space. This is achieved using a kernel function.