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Optimization-Based Visualization

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Multidimensional Data Visualization

Part of the book series: Springer Optimization and Its Applications ((SOIA,volume 75))

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Abstract

In this chapter, we consider one of themost popular approaches of multidimensional data visualization, known as multidimensional scaling (MDS) [14, 31, 127, 139, 150, 191, 202]. The essential part of this technique is optimization of a function possessing many optimization adverse properties [231]. By means of MDS, a set of objects can be represented as a set of points in a low-dimensional space and exposed in this way to a human expert for a heuristic analysis. The data for MDS is a pairwise similarity/dissimilarity between the objects—it is not necessary to have multidimensional points as data. Application areas of MDS vary from psychometrics [197] and market analysis [39, 165] to mobile communications [75] and pharmacology [232].

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  1. Institute of Mathematics and Informatics, Vilnius University, Vilnius, Lithuania

    Gintautas Dzemyda, Olga Kurasova & Julius Žilinskas

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  1. Gintautas Dzemyda
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  2. Olga Kurasova
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Dzemyda, G., Kurasova, O., Žilinskas, J. (2013). Optimization-Based Visualization. In: Multidimensional Data Visualization. Springer Optimization and Its Applications, vol 75. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-0236-8_3

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