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arXiv · 1702.01226

Towards Better Analysis of Machine Learning Models: A Visual Analytics Perspective

Shixia Liu·Xiting Wang·Mengchen Liu·Jun Zhu
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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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BibTeXRIS

Shixia Liu, Xiting Wang, Mengchen Liu, Jun Zhu. 2017-02-04. Towards Better Analysis of Machine Learning Models: A Visual Analytics Perspective. https://arxiv.org/abs/1702.01226

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