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Proceedings Paper

Visual analysis of multidimensional data using fast MDS algorithm
Author(s): Piotr Pawliczek; Witold Dzwinel
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Paper Abstract

We discuss here an improved multidimensional scaling (MDS) algorithm allowing for fast and accurate visualization of multidimensional clusters. Unlike in traditional approaches we use a natural heuristics - N-body solver - for extracting the global minimum of the multidimensional, multimodal and nonlinear "stress function". As was shown earlier, the method is very reliable avoiding stuck the solver in local minima. We focus on decreasing the time complexity of the algorithm from Ω(N2) to O(N2) by eliminating from computations most of distances, which are irrelevant in reproducing the real cluster structure in low dimensional spaces. This way we can speed up MDS algorithm significantly (even in order of magnitude for large datasets) allowing for interactive immersion into the data by immediate on-screen manipulation on different data representations.

Paper Details

Date Published: 28 December 2007
PDF: 11 pages
Proc. SPIE 6937, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2007, 69372M (28 December 2007); doi: 10.1117/12.784772
Show Author Affiliations
Piotr Pawliczek, AGH Univ. of Science and Technology (Poland)
Witold Dzwinel, AGH Univ. of Science and Technology (Poland)


Published in SPIE Proceedings Vol. 6937:
Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2007

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