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Vis Inf  2017, Vol. 1 Issue (1): 48-56    DOI: 10.1016/j.visinf.2017.01.006
论文     
机器学习模型的可视分析
Shixia Liu, Xiting Wang, Mengchen Liu, Jun Zhu
Tsinghua University, Beijing, China
Towards better analysis of machine learning models: A visual analytics perspective
Shixia Liu, Xiting Wang, Mengchen Liu, Jun Zhu#br#
1 Tsinghua University, Beijing, China
 全文: PDF 
摘要: 背景:交互式模型分析是一个借助交互可视化技术来理解、诊断和改进机器学习模型的过程,它可以帮助用户有效地解决现实世界中的人工智能和数据挖掘问题。大数据分析技术的迅速发展引发了各种各样的交互式模型分析任务。

贡献:我们对这一迅速发展的领域进行了全面的分析,将相关工作划分为三类:理解、诊断和改进。每一类都以最近有影响力的工作为例,同时探讨了今后潜在的研究方向。

关键词: 交互模型分析交互式可视化机器学习理解诊断精炼    
Abstract:
Interactive model analysis, the process of understanding, diagnosing, and refining a machine learning model with the help of interactive visualization, is very important for users to efficiently solve real-world artificial intelligence and data mining problems. Dramatic advances in big data analytics have led to a wide variety of interactive model analysis tasks. In this paper, we present a comprehensive analysis and interpretation of this rapidly developing area. Specifically, we classify the relevant work into three categories: understanding, diagnosis, and refinement. Each category is exemplified by recent influential work. Possible future research opportunities are also explored and discussed.
Key words: Interactive model analysis    Interactive visualization    Machine learning    Understanding    Diagnosis    Refinement
出版日期: 2017-07-06
通讯作者: Shixia Liu     E-mail: shixia@tsinghua.edu.cn
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Shixia Liu, Xiting Wang, Mengchen Liu, Jun Zhu. Towards better analysis of machine learning models: A visual analytics perspective. Vis Inf, 2017, 1(1): 48-56.

链接本文:

http://www.zjujournals.com/vi/CN/10.1016/j.visinf.2017.01.006        http://www.zjujournals.com/vi/CN/Y2017/V1/I1/48

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