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Uncertainty Modelling in Data Science

Produktform: E-Buch Text Elektronisches Buch in proprietärem

Over recent decades, interest in extensions and alternatives to probability and statistics has increased significantly in diverse areas, including decision-making, data mining and machine learning, and optimisation. This interest stems from the need to enrich existing models, in order to include different facets of uncertainty, like ignorance, vagueness, randomness, conflict or imprecision. Frameworks such as rough sets, fuzzy sets, fuzzy random variables, random sets, belief functions, possibility theory, imprecise probabilities, lower previsions, and desirable gambles all share this goal, but have emerged from different needs. weiterlesen

Dieser Artikel gehört zu den folgenden Serien

Elektronisches Format: PDF

Sprache(n): Englisch

ISBN: 978-3-319-97547-4 / 978-3319975474 / 9783319975474

Verlag: Springer International Publishing

Erscheinungsdatum: 24.07.2018

Seiten: 234

Herausgegeben von María Angeles Gil, Przemyslaw Grzegorzewski, Olgierd Hryniewicz, Thierry Denoeux, Sébastien Destercke

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