Dataset visualization based on a simulation of intermolecular forces. Jan Drchal, Pavel Kordik, Miroslav Snorek. IWIM, Prague, 2007.
Article (in pdf)
Abstract. The visualization is an important technique used in many stages of data mining process. This article deals mostly with visualization for preprocessing purposes. The aim of our approach is to visualize distances (Euclidean or others) between data samples. This can be helpful when taking picture of data clustering. In classification tasks it can be used to select outlayer for removal. In this paper we present a novel way of such visualization which is based on a physical system simulation. It is inspired by intermolecular forces and employs overall energy minimization. This minimization is done via known unconstrained optimization numerical methods such as Steepest Descent, Conjugated Gradients or Quasi-Newton. The proposed algorithm was originally designed and was found useful when interpretting diversity in evolutionary algorithms. Here, we show its properties on well-known datasets Iris and Ecoli.
Keywords. Data mining, visualization, optimization.
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