The Choquet kernel for monotone data
نویسندگان
چکیده
In this paper, we introduce a kernel for monotone data derived from the Choquet integral with its underlying fuzzy measure. While a naïve computation of this kernel has a complexity that is exponential in the number of data attributes, we propose a more efficient approach with quadratic time complexity. Kernel PCA and SVM classification are employed to illustrate characteristics and benefits of the new Choquet kernel in two experiments related to decision-making and pricing.
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