@inproceedings{Schneider2016Indiv-35315,
  year={2016},
  doi={10.2312/eurp.20161130},
  title={When Individual Data Points Matter : Interactively Analysing Classification Landscapes},
  isbn={978-3-03868-015-4},
  publisher={The Eurographics Association},
  booktitle={EuroVis 2016 - Posters},
  editor={Isenberg, Tobias and Sadlo, Filip},
  author={Schneider, Bruno and Mittelstädt, Sebastian and Keim, Daniel A.}
}

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    <dcterms:abstract xml:lang="eng">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.</dcterms:abstract>
    <dcterms:issued>2016</dcterms:issued>
    <dc:creator>Keim, Daniel A.</dc:creator>
    <dc:contributor>Schneider, Bruno</dc:contributor>
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    <dc:contributor>Keim, Daniel A.</dc:contributor>
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