Towards Better Analysis of Machine Learning Models: A Visual Analytics Perspective
February 04, 2017 ยท Declared Dead ยท ๐ Visual Informatics
"No code URL or promise found in abstract"
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Authors
Shixia Liu, Xiting Wang, Mengchen Liu, Jun Zhu
arXiv ID
1702.01226
Category
cs.LG: Machine Learning
Cross-listed
stat.ML
Citations
387
Venue
Visual Informatics
Last Checked
3 months ago
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 has 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.
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