Abstract
We investigate multidimensional scaling with Bregman divergences and show that the Sammon mapping can be thought of as a truncated Bregman multidimensional scaling (BMDS). We show that the full BMDS improves upon the Sammon mapping on some standard data sets and investigate the reasons underlying this improvement. We then introduce two families of BMDS which use opposite strategies to create good mappings of standard data sets and investigate these opposite strategies analytically.
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Sun, J., Crowe, M., Fyfe, C. (2010). Extending Metric Multidimensional Scaling with Bregman Divergences. In: García-Pedrajas, N., Herrera, F., Fyfe, C., Benítez, J.M., Ali, M. (eds) Trends in Applied Intelligent Systems. IEA/AIE 2010. Lecture Notes in Computer Science(), vol 6097. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13025-0_63
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DOI: https://doi.org/10.1007/978-3-642-13025-0_63
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13024-3
Online ISBN: 978-3-642-13025-0
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