论文标题
用于机器学习的视觉分析技术的调查
A Survey of Visual Analytics Techniques for Machine Learning
论文作者
论文摘要
用于机器学习的视觉分析最近已发展为可视化领域中最令人兴奋的领域之一。为了更好地确定哪些研究主题是有希望的，并学习如何在视觉分析中应用相关技术，我们会系统地审查过去十年中与2010年之前发表的259篇论文。我们在2010年之前与代表性作品一起发表。我们构建了一个分类学类别，其中包括三个一级类别：包括模型构建之前的技术，在模型构建过程中，在模型建立型号和模型之后的技术。每个类别都以代表性分析任务为特征，每个任务都以一组最新的有影响力的作品为例。我们还讨论并强调了研究挑战，并有希望对视觉分析研究人员有用的潜在潜在研究机会。
Visual analytics for machine learning has recently evolved as one of the most exciting areas in the field of visualization. To better identify which research topics are promising and to learn how to apply relevant techniques in visual analytics, we systematically review 259 papers published in the last ten years together with representative works before 2010. We build a taxonomy, which includes three first-level categories: techniques before model building, techniques during model building, and techniques after model building. Each category is further characterized by representative analysis tasks, and each task is exemplified by a set of recent influential works. We also discuss and highlight research challenges and promising potential future research opportunities useful for visual analytics researchers.
