TY  - CHAP
ID  - rehm_clustervis_2007
T1  - Single Cluster Visualization to Optimize Air Traffic Management
A1  - Rehm, Frank
A1  - Klawonn, Frank
A1  - Kruse, Rudolf
ED  - Lenz, Hans-Joachim
ED  - Decker, Reinhold
TI  - Advances in Data Analysis
Y1  - 2007
SP  - 319
EP  - 325
PB  - Springer
SN  - 978-3-540-70980-0
M2  - doi: 10.1007/978-3-540-70981-7_36
KW  - bibtex-import
N2  - 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.
M1  - citeulike-article-id={1995904}
M1  - 
priority={0}
ER  -