Abstract
Multidimensional scaling provides dimensionality reduction for high-dimensional data. Most of the available techniques try to preserve similarity in terms of distances between data objects. In this paper a new approach is proposed that extends the distance preserving aspect by means of density preservation. Combining both, the distance aspect and the density aspect, permits efficient multidimensional scaling solutions.
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References
BORG, I. and GROENEN, P. (2005): Modern Multidimensional Scaling: Theory and Applications. Springer, Berlin.
Chalmers, M. (1996): A Linear Iteration Time Layout Algorithm for Visualising High-Dimensional Data. In Proceedings of IEEE Visualization 1996, San Francisco, CA, 127–132.
FORINA, M., LEARDI, R., ARMANINO, C. and LANTERI, S. (1988): PARVUS: An Extendable Package of Programs for Data Exploration, Classification and Correlation. Elsevier, Amsterdam.
KRUSKAL, J.B. and WISH, M. (1978): Multidimensional Scaling. Sage. Beverly Hills.
Lesot, M.J., Rehm, F., Klawonn, F. and Kruse, R. (2006): Prediction of Aircraft Flight Duration. In Proceedings of the 11th IFAC Symposium on Control in Transportation Systems, Delft, 107–112.
MORRISON, A., ROSS, G. and CHALMERS, M. (2003): Fast Multidimensional Scaling through Sampling, Springs and Interpolation. Information Visualization, 2, 68–77.
Rehm, F., Klawonn, F. and Kruse, R. (2006): POLARMAP – Efficient Visualisation of High Dimensional Data. In IEEE Proceedings of the 10th International Conference on Information Visualisation, London, 731–740.
Williams, M. and Munzner, T. (2004): Steerable, Progressive Multidimensional Scaling. In Proceedings of the 10th IEEE Symposium on Information Visualization, Austin, TX, 57–64.
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© 2009 Springer-Verlag Berlin Heidelberg
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Rehm, F., Klawonn, F., Kruse, R. (2009). Density-Based Multidimensional Scaling. In: Gaul, W., Bock, HH., Imaizumi, T., Okada, A. (eds) Cooperation in Classification and Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00668-5_5
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DOI: https://doi.org/10.1007/978-3-642-00668-5_5
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