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ParallAX — A data mining tool based on parallel coordinates

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Summary

ParallAX is a new user-friendly tool for visualizing and analyzing multivariate data using the parallel coordinates methodology. Complex queries are formed as logical combinations of a small number of atomic queries. Pre-processing facilities like banding, outlier-pruning, constrained permutations selection, wrapping and others are included. These and some more features are the basis towards automated search processes which are essential when categorizing data. In addition, the parallel coordinates display is dynamically linked to scatter plot displays, where the results of complex polygonal queries on one display are reflected on the other.

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References

  • Inselberg, A. & Dimsdale, B. (1990), ‚Parallel Coordinates: A Tool for Visualizing Multidimensional Geometry‘, Proc. of IEEE Conf. on Visualization, 361–378.

  • Chernoff, H. (1973), ‚The use of faces to represent points in k-dimensional space graphically‘, J. Am. Stat. Assoc. 68, 361–368.

    Article  Google Scholar 

  • Martin, R. & Ward, M.O. (1995), ‚High dimensional brushing for interactive exploration of multivariate data‘, Proc. IEEE Conf. on Visualization, Atlanta, GA, 271–278.

  • Ward, M.O. (1994), ‚XmdvTool: integrating multiple methods for visualizing multivariate data‘, Proc. IEEE Conf. on Visualization, San Jose, CA, 326–333.

  • Schmid, C. & Hinterberger, H. (1994), ‚Comparative Multivariate Visualization Across Conceptually Different Graphic Displays‘, Proc. of 7th SSDBM, IEEE Comp. Soc., Los Alamitos, CA.

  • Fayyad, U. M., Piatetsky-Shapiro, G., Smyth, P. & Uthurusamy, R. (1996), ‚Advances in Knowledge Discovery and Data Mining‘, AAAI Press / The MIT Press.

  • Wegman, E. J. (1990), ‚Hyperdimensional Data Analysis Using Parallel Coordinates‘, J. of the American Statistical Association, Vol.85, No. 411.

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Authors and Affiliations

  1. Faculty of Exact Sciences, Tel Aviv University, Ramat Aviv, Tel Aviv, 69978, Israel

    Tova Avidan & Shlomo Avidan

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  1. Tova Avidan
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  2. Shlomo Avidan
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Correspondence to Tova Avidan.

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Avidan, T., Avidan, S. ParallAX — A data mining tool based on parallel coordinates. Computational Statistics 14, 79–89 (1999). https://doi.org/10.1007/PL00022707

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  • DOI: https://doi.org/10.1007/PL00022707

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