Machine Learning Methods in Visualisation for Big Data 2018

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https://diglib.eg.org/handle/10.2312/2632403

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Browsing Machine Learning Methods in Visualisation for Big Data 2018 by Subject "Visualization theory"

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    Panning for Insight: Amplifying Insight through Tight Integration of Machine Learning, Data Mining, and Visualization
    (The Eurographics Association, 2018) Karer, Benjamin; Scheler, Inga; Hagen, Hans; Ian Nabney and Jaakko Peltonen and Daniel Archambault
    With the rapid progress made in Data Mining, Visualization, and Machine Learning during the last years, combinations of these methods have gained increasing interest. This paper summarizes ideas behind ongoing work on combining methods of these three domains into an insight-driven interactive data analysis workflow. Based on their interpretation of data visualizations, users generate metadata to be fed back into the analysis. The resulting resonance effect improves the performance of subsequent analysis. The paper outlines the ideas behind the workflow, indicates the benefits and discusses how to avoid potential pitfalls.