In this paper we address the problem of visualizing in a bounded region a set of individuals, which has attached a dissimilarity measure and a statistical value, as convex objects. This problem, which extends the standard Multidimensional Scaling Analysis, is written as a global optimization problem whose objective is the difference of two convex functions (DC). Suitable DC decompositions allow us to use the Difference of Convex Algorithm (DCA) in a very efficient way. Our algorithmic approach is used to visualize two real-world datasets.
Bibliographical noteEpub ahead of print. Published online: 28. April 2017
- Data visualization
- DC functions
- DC algorithm
- Multidimensional scaling analysis
Carrizosa, E., Guerrero, V., & Romero Morales, D. (2018). Visualizing Data as Objects by DC (Difference of Convex) Optimization. Mathematical Programming, 169(1), 119-140. https://doi.org/10.1007/s10107-017-1156-1