Single Cluster Visualization to Optimize Air Traffic Management
Type of publication: | Incollection |
Citation: | rehm_clustervis_2007 |
Booktitle: | Advances in Data Analysis |
Year: | 2007 |
Pages: | 319--325 |
Publisher: | Springer |
ISBN: | 978-3-540-70980-0 |
DOI: | 10.1007/978-3-540-70981-7_36 |
Abstract: | In this paper we present an application of single cluster visualization (SCV) a technique to visualize single clusters of high-dimensional data. This method maps a single cluster to the plane trying to preserve the relative distances of feature vectors to the corresponding prototype vector. Thus, fuzzy clustering results representing relative distances in the form of a partition matrix as well as hard clustering partitions can be visualized with this technique. The resulting two-dimensional scatter plot illustrates the compactness of a certain cluster and the need of additional prototypes as well. In this work, we will demonstrate the visualization method on a practical application. |
Userfields: | citeulike-article-id={1995904}, priority={0}, |
Keywords: | bibtex-import |
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Added by: | [ADM] |
Total mark: | 0 |
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