Optimization-Based Visualization

Gintautas Dzemyda, Olga Kurasova and Julius Žilinskas
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Gintautas Dzemyda: Vilnius University
Olga Kurasova: Vilnius University
Julius Žilinskas: Vilnius University

Chapter Chapter 3 in Multidimensional Data Visualization, 2013, pp 41-112 from Springer

Abstract: 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].

Keywords: Multidimensional Point; City Block Distance; Explicit Enumeration; Lower Level Problem; Local Minimization Algorithm (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-1-4419-0236-8_3

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DOI: 10.1007/978-1-4419-0236-8_3

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