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Combining implicational quantifiers for equivalence ones by fuzzy connectives

机译:用模糊连词组合等价的含蕴量词

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Relations between two Boolean attributes derived from data can be quantified by truth functions defined on fourfold tables corresponding to pairs of the attributes. Several classes of such quantifiers (implicational, double implicational, and equivalence ones) with truth values in the unit interval were investigated in the frame of the theory of data mining methods. The definition of double implicational quantifiers is based on the idea of conjunction of both directions implications (similarly for equivalence). In the fuzzy logic theory, there are well-defined classes of fuzzy operators, namely t-norms representing various types of evaluations of fuzzy conjunction (and t-conorms representing fuzzy disjunction). I assert that each t-norm applied to an implicational quantifier gives a double implicational quantifier. Analogously, each t-conorm applied to a double implicational quantifier gives an equivalence quantifier. Logical properties of obtained quantifiers are discussed. The method is illustrated by examples of well-known quantifiers and operators. (c) 2006 Wiley Periodicals, Inc.
机译:可以通过在对应于属性对的四重表上定义的真函数来量化从数据派生的两个布尔属性之间的关系。在数据挖掘方法的理论框架内,研究了几类具有单位间隔真值的此类量词(隐含,双蕴涵和等价的)。双重蕴涵量词的定义是基于两个方向的蕴涵相结合的思想(对于等价的相似)。在模糊逻辑理论中,存在明确定义的模糊算子类别,即表示各种类型的模糊合取的t范数(和表示模糊析取的t范式)。我断言,应用于蕴涵量词的每个t范数都给出了一个双重蕴涵量。类似地,应用于双重蕴涵量词的每个t-conorm都给出了一个等效量词。讨论了获得的量词的逻辑性质。通过众所周知的量词和运算符的示例来说明该方法。 (c)2006年Wiley Periodicals,Inc.

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