A knowledge base is an important notion of rough set theory. A tolerance knowledge base is its generalization. Measures of uncertainty as important evaluation tools in the fields of machine learning can measure the dependence and similarity between two targets. This paper investigates uncertainty measurement for a tolerance knowledge base by using its knowledge structure. The knowledge structure of a given tolerance knowledge base is first introduced by means of set vectors. Then, the dependence and independence between knowledge structures of tolerance knowledge bases are depicted. Next, the measurement uncertainty of tolerance knowledge bases is investigated. Finally, to obtain two tolerance knowledge bases with additional data, two information systems from the UCI Repository of machine learning databases are selected to construct two numerical experiments, and an effectiveness analysis is performed from the perspective of statistics to show the feasibility of the proposed measures.

中文翻译：

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公差知识库的不确定度测量

知识库是粗糙集理论的一个重要概念。公差知识库是它的概括。不确定性度量作为机器学习领域的重要评估工具，可以衡量两个目标之间的相关性和相似性。本文利用其知识结构研究了公差知识库的不确定性度量。首先通过集合向量的方式引入给定容差知识库的知识结构。然后，描述了容忍知识库的知识结构之间的依赖和独立性。接下来，研究了公差知识库的测量不确定度。最后，要获得两个带有附加数据的公差知识库，