Reduction of attributes in an information system (IS) is a basic step for IS analysis. The original rough set model of Pawlak depends on an equivalence relation which is strongly constraints. This paper aims to use similarity classes and similarity degrees to obtain a reduction of IS and indicate an approach by using an example from biochemistry to get a quantitative structure activity relationship (QSAR). Moreover, signs of each attribute and degrees of memberships are computed to give a decision by using the degree of similarity. The suggested approach gives an increase in decision-making and decision accuracy.

中文翻译：

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基于相似性和决策的减少

减少信息系统 (IS) 中的属性是 IS 分析的基本步骤。Pawlak 的原始粗糙集模型依赖于强约束的等价关系。本文旨在使用相似类和相似度来获得 IS 的减少，并通过使用生物化学中的一个例子来说明一种获得定量结构活性关系 (QSAR) 的方法。此外，通过使用相似度计算每个属性的符号和隶属度以给出决策。建议的方法提高了决策制定和决策的准确性。