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Point Information Gain and Multidimensional Data Analysis
Version 1
: Received: 16 October 2016 / Approved: 17 October 2016 / Online: 17 October 2016 (11:35:13 CEST)
A peer-reviewed article of this Preprint also exists.
Rychtáriková, R.; Korbel, J.; Macháček, P.; Císař, P.; Urban, J.; Štys, D. Point Information Gain and Multidimensional Data Analysis. Entropy 2016, 18, 372. Rychtáriková, R.; Korbel, J.; Macháček, P.; Císař, P.; Urban, J.; Štys, D. Point Information Gain and Multidimensional Data Analysis. Entropy 2016, 18, 372.
Abstract
We generalize the point information gain (PIG) and derived quantities, i.e., point information gain entropy (PIE) and point information gain entropy density (PIED), for the case of the Rényi entropy and simulate the behavior of PIG for typical distributions. We also use these methods for the analysis of multidimensional datasets. We demonstrate the main properties of PIE/PIED spectra for the real data on the example of several images, and discuss further possible utilizations in other fields of data processing.
Keywords
point information gain; Rényi entropy; data processing
Subject
Computer Science and Mathematics, Applied Mathematics
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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