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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
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.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-3-642-00668-5_5
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-00667-8
Online ISBN: 978-3-642-00668-5
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)