论文标题
视觉分析和人类参与机器学习
Visual Analytics and Human Involvement in Machine Learning
论文作者
论文摘要
快速开发的AI系统和应用仍需要人类参与分析过程的所有部分。人类的决策主要基于可视化，从而为数据科学家提供了数据属性的详细信息和分析程序的结果。在机器学习（ML）过程的不同步骤中使用了不同的可视化。可视化使用的决定取决于因素，例如数据域，数据模型和ML过程中的步骤。在本章中，我们描述了ML过程中的七个步骤，并查看与不同类型的数据，模型和目的的不同步骤相关的不同可视化技术。
The rapidly developing AI systems and applications still require human involvement in practically all parts of the analytics process. Human decisions are largely based on visualizations, providing data scientists details of data properties and the results of analytical procedures. Different visualizations are used in the different steps of the Machine Learning (ML) process. The decision which visualization to use depends on factors, such as the data domain, the data model and the step in the ML process. In this chapter, we describe the seven steps in the ML process and review different visualization techniques that are relevant for the different steps for different types of data, models and purposes.
