kernel_computation() Clause Samples

kernel_computation(). The dual formulation of the SVM optimization problem introduces the notion of the kernel. In the case of linearly separable data, the kernel of two vectors is equivalent to the dot product of these two vectors. However, if we are dealing with non-separable data the kernel can be defined by a variety of functions. For instance, there is the polynomial kernel, the Gaussian kernel, the Laplacian kernel and others. The efficiency of a kernel function is determined by the nature of the training and tested input data, as well as other factors such as speed and accuracy. Hence, we selected a kernel function that was suitable for our training data set. In particular, we chose the exponential kernel function which according to the equivalent software implementation of this function is computed based on the following formula: