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On Spatio-Temporal Data Modelling and Uncertainty Quantification Using Machine Learning and Information Theory - Springer Theses Fabian Guignard 2022 edition
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On Spatio-Temporal Data Modelling and Uncertainty Quantification Using Machine Learning and Information Theory - Springer Theses
Fabian Guignard
Particular attention is also paid to a highly versatile exploratory data analysis tool based on information theory, the Fisher-Shannon analysis, which can be used to assess the complexity of distributional properties of temporal, spatial and spatio-temporal data sets.
158 pages, 43 Illustrations, color; 25 Illustrations, black and white; XVIII, 158 p. 68 illus., 43 i
| Médium | Knihy Paperback Book (Kniha s mäkkou väzbou a lepeným chrbtom) |
| Vydané | 13. marca 2023 |
| ISBN13 | 9783030952334 |
| Vydavatelia | Springer Nature Switzerland AG |
| Strany | 158 |
| Rozmery | 150 × 220 × 10 mm · 279 g |
| Jazyk | Nemčina |
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