Reordering dimensions for Radial Visualization of multidimensional data — A Genetic Algorithms approach

In this paper, we propose a Genetic Algorithm (GA) for solving the problem of dimensional ordering in Radial Visualization (Radviz) systems. The Radviz is a non-linear projection of high-dimensional data set onto two dimensional space. The order of dimension anchors in the Radviz system is crucial for the visualization quality. We conducted experiments on five common data sets and compare the quality of solutions found by GA and those found by the other well-known methods. The experimental results show that the solutions found by GA for these tested data sets are very competitive having better cost values than almost all solutions found by other methods. This suggests that GA could be a good approach to solve the problem of dimensional ordering in Radviz.