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    When Individual Data Points Matter: Interactively Analysing Classification Landscapes

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    Date
    2016
    Author
    Schneider, Bruno
    Mittelstädt, Sebastian
    Keim, Daniel A. ORCID
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    Abstract
    The selection of classification models among several options with similar accuracy cannot be done through purely automated methods, and especially in scenarios in which the cost of misclassified instances is crucial, such as criminal intelligence analysis. To tackle this problem and illustrate our ideas, we developed a prototype for the visualization and comparison of classification landscapes. In our system, the same data is given to different classification models. Classification landscapes are shown in the scatter plots, together with their geographical location on a map and detailed textual description for each data record. To enhance model comparison, we implemented interactive anchor-points selection in classification landscapes. Using those anchors, the user can manipulate and reproject the model results in order to get more comparable classification landscapes. We provided a use case with crime data, for crime intelligence analysis.
    BibTeX
    @inproceedings {10.2312:eurp.20161130,
    booktitle = {EuroVis 2016 - Posters},
    editor = {Tobias Isenberg and Filip Sadlo},
    title = {{When Individual Data Points Matter: Interactively Analysing Classification Landscapes}},
    author = {Schneider, Bruno and Mittelstädt, Sebastian and Keim, Daniel A.},
    year = {2016},
    publisher = {The Eurographics Association},
    ISSN = {-},
    ISBN = {978-3-03868-015-4},
    DOI = {10.2312/eurp.20161130}
    }
    URI
    http://dx.doi.org/10.2312/eurp.20161130
    https://diglib.eg.org:443/handle/10
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    Eurographics Association copyright © 2013 - 2022 
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    Theme by @mire NV
    System hosted at  Graz University of Technology.
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