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A functional causal model based on a classifier, i.e., X_i = f(PA_i, N_i). Here, N_i follows a uniform distribution on [0, 1] and is used to randomly sample a class (category) using the conditional ...

Abstract: There are excessive and disordered rules generated by traditional approaches of association rule mining, many of which are redundant, so that they are difficult for users to understand and ...

Abstract: Most conventional techniques for estimating conditional probability densities are inappropriate for applications involving periodic variables. In this paper we introduce three related ...