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Fast evaluation of t-norms for fuzzy association rules mining

机译:模糊关联规则挖掘的t模快速评估

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The aim of this paper is to present a bitwise approach on evaluation of fuzzy t-norms. T-norms are functions that generalize the notion of conjunction, and as such play an important role in fuzzy association rule mining process. Efficient algorithms for batch evaluation of the most common t-norms is proposed that minimizes computation time as well as memory space requirements at the cost of user-adjustable loss of precision of the membership degrees.
机译:本文的目的是提出一种评估模糊t范数的按位方法。 T范数是泛化连接概念的函数,因此在模糊关联规则挖掘过程中起着重要作用。提出了用于最常见t范数的批处理评估的有效算法,该算法以用户可调整的隶属度精度损失为代价,将计算时间和存储空间需求减至最少。

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