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A fuzzy set-based accuracy assessment of soft classification

机译:基于模糊集的软分类精度评估

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摘要

Despite the sizable achievements obtained, the use of soft classifiers is still limited by the lack of well-assessed and adequate methods for evaluating the accuracy of their outputs. This paper proposes a new method that uses the fuzzy set theory to extend the applicability of the traditional error matrix method to the evaluation of soft classifiers. It is designed to cope with those situations in which classification and/or reference data are expressed in multimembership form and the grades of membership represent different levels of approximation to intrinsically vague classes.
机译:尽管取得了相当大的成就,但由于缺乏评估效果和评估其准确性的适当方法,软分类器的使用仍然受到限制。提出了一种利用模糊集理论将传统误差矩阵法的适用范围扩展到软分类器评估的新方法。它旨在应对那些以多成员身份形式表示分类和/或参考数据并且成员等级代表本质上模糊的类的不同近似级别的情况。

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