A survey of visual analytics techniques for machine learning

• 作者: Jun Yuan Changjian Chen Weikai Yang Mengchen Liu Jiazhi Xia Shixia Liu
• 来源期刊: 计算可视媒体（英文版）
• 年，卷（期）: 2021,（1）
• 所属期刊栏目: REVIEW ARTICLE
• 页码范围: 3-36
• 页数: 34页
• 语种: 英文

摘要

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 modeling 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.