The Choquet Kernel for Monotone Data
Ali Fallah Tehrani, Marc Strickert, Eyke Hüllermeier · 2014
Abstract. In this paper, we introduce a kernel for monotone data de-rived 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 em-ployed to illustrate characteristics and benefits of the new Choquet kernel in two experiments related to decision-making and pricing.