Multi-output Suppport Vector Regression
نویسندگان
چکیده
Support vector regression builds a model of a process that depends on a set of factors. It traditionally considers one output at a time, which means that advantage cannot be taken of the correlations that may exist between outputs. The purpose of this paper is to show how the body of knowledge accumulated by geostatisticians on Kriging and its extensions over the last 40 years can help extend support vector regression to the multi-output case and provides guidance for the choice of a suitable kernel for a given application, a recurrent, fundamental and largely open question.
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