论文标题
使用知识图的基于计算规则的机器学习分类器的解释
Computing Rule-Based Explanations of Machine Learning Classifiers using Knowledge Graphs
论文作者
论文摘要
使用符号知识表示和推理作为解决机器学习分类器缺乏透明度的一种方法，这是一个研究领域，最近吸引了许多研究人员。在这项工作中，我们使用知识图作为基础框架，该框架提供了代表机器学习分类器操作的解释的术语。特别是，给定对分类器的应用域的描述，以知识图的形式进行了描述，我们引入了一种新颖的方法，用于提取和表示其操作的黑盒说明，以知识图的术语表达的一阶逻辑规则的形式。
The use of symbolic knowledge representation and reasoning as a way to resolve the lack of transparency of machine learning classifiers is a research area that lately attracts many researchers. In this work, we use knowledge graphs as the underlying framework providing the terminology for representing explanations for the operation of a machine learning classifier. In particular, given a description of the application domain of the classifier in the form of a knowledge graph, we introduce a novel method for extracting and representing black-box explanations of its operation, in the form of first-order logic rules expressed in the terminology of the knowledge graph.
