Classification Using the Zipfian Kernel

Abstrakt

We propose to use the Zipfian distribution as a kernel for design of a nonparametric classifier in contrast to the Gaussian distribution used in most of kernel methods. We show that the Zipfian distribution takes into account multifractal nature of data and gives a true picture of scaling properties inherent in data. We also show that this new look at data structure can lead to a simple classifier that can, for some tasks, outperform more complex systems.