A Kernel Defined over Qualitative Spaces of Orders of Magnitude
نویسندگان
چکیده
This paper lies within the domain of learning algorithms based on kernels of Support Vector Machines. A kernel is constructed over the discrete structure of absolute orders of magnitude spaces. This kernel is based on an explicit function, defined from the space of k-tuples of qualitative labels to a feature space, which captures the remoteness between the components of the patterns by using certain weights exponentially. A simple example that allows interpreting the kernel in terms of proximity of the patterns is presented.
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