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Visualization of data: methods, software, and applications. (English) Zbl 1442.62769
Singh, Vinai K. (ed.) et al., Advances in mathematical methods and high performance computing. Cham: Springer. Adv. Mech. Math. 41, 295-307 (2019).
Summary: Visualization is a part of data science, and essential to enable sophisticated analysis of data. The visualization ensures the human participation in most decisions when analyzing data. In this paper, we review methods and software for visualization of multidimensional data. The emphasis is put on the web-based DAMIS solution for data analysis, allowing researchers to carry out the primary data analysis and to investigate the projection of multidimensional data on a plane, the similarities between the data items, the influence of individual features, and their relationships by visual analysis techniques, using the high-performance computing resources. DAMIS is applied to the visual efficiency analysis of regional economic development to evaluate how regional resources are reflected in the economic results. The projection methods (principal component analysis, multidimensional scaling) and artificial neural networks (self-organizing map, SAMANN) are the core strategies for the analysis.
For the entire collection see [Zbl 06982489].

MSC:
62R07 Statistical aspects of big data and data science
62A09 Graphical methods
62H25 Factor analysis and principal components; correspondence analysis
62M45 Neural nets and related approaches to inference from stochastic processes
62P20 Applications of statistics to economics
62-08 Computational methods for problems pertaining to statistics
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