Linear Discriminative Star Coordinates for Exploring Class and Cluster Separation of High Dimensional DataEI

    Cited by: 7|Bibtex|6|

    Comput. Graph. Forum, Volume 36, Issue 3, 2017, Pages 401-410.


    One main task for domain experts in analysing their nD data is to detect and interpret class/cluster separations and outliers. In fact, an important question is, which features/dimensions separate classes best or allow a cluster-based data classification. Common approaches rely on projections from nD to 2D, which comes with some challenge...More
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