Abstract
Parallel coordinate plot is a convenient method for presenting a set of multivariate data points in simple two-dimensional form. Each data point is represented by a horizontal segment line connecting vertical axes corresponding to subsequent variables. Another very convenient method for representing multivariate data is their visualisation by use of self-organizing maps. Both methods were applied for visualisation of the differences between two sets of data representing randomly distorted letters printed in different fonts. Each letter was characterized by 16 statistical features.
We wanted to observe how much differ the positions occupied by samples of these letters when viewed in sixteen-dimensional feature space. We will show the plots visualising the locations of the pairs of letters: I&W and F&J. We came to conclusion that the introduced visualisation methods complement each other.
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Szustalewicz, A. (2002). Visualisation of multivariate data using parallel coordinate plots and Kohonen’s SOM’s. Which is better?. In: Sołdek, J., Pejaś, J. (eds) Advanced Computer Systems. The Springer International Series in Engineering and Computer Science, vol 664. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-8530-9_7
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DOI: https://doi.org/10.1007/978-1-4419-8530-9_7
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