The nearest-neighbour classifier assigns a new input vector x to the same class as that of the nearest input vector xn from the training set, where in the simplest case, the distance is defined by the Euclidean metric || x - x_n ||^2. By expressing this rule in terms of scalar products and then making use of kernel substitution, formulate the nearest-neighbour classifier for a general nonlinear kernel.

The nearest-neighbour classifier assigns a new input vector x to the same class as that of the nearest input vector Xn from the training set, where in the simplest case, the distance is defined by the Euclidean metric Ix - xl2. By expressing this rule in terms of scalar products and then making use of kernel substitution, formulate the nearest-neighbour classifier for a general nonlinear kernel The nearest-neighbour classifier assigns a new input vector x to the same class as that of the nearest input vector Xn from the training set, where in the simplest case, the distance is defined by the Euclidean metric Ix - xl2. By expressing this rule in terms of scalar products and then making use of kernel substitution, formulate the nearest-neighbour classifier for a general nonlinear kernel