LEADER 03571nam a22005655i 4500001 99129136328906421 005 20230717143446.0 006 m o d | 007 cr cnu|||||||| 008 220824s2023 sz | o |||| 0|eng d 020 3-031-15509-2 024 7 10.1007/978-3-031-15509-3 |2doi 035 (MiAaPQ)EBC7077637 035 (Au-PeEL)EBL7077637 035 (CKB)24739662200041 035 (DE-He213)978-3-031-15509-3 035 (PPN)264193040 035 (EXLCZ)9924739662200041 040 MiAaPQ |beng |erda |epn |cMiAaPQ |dMiAaPQ 050 4 QA76.9.S63 |b.B855 2023 072 7 UN |2bicssc 072 7 COM018000 |2bisacsh 072 7 UN |2thema 082 0 006.3 |223 082 519.5 245 10 Building Bridges between Soft and Statistical Methodologies for Data Science / |cedited by Luis A. García-Escudero, Alfonso Gordaliza, Agustín Mayo, María Asunción Lubiano Gomez, Maria Angeles Gil, Przemyslaw Grzegorzewski, Olgierd Hryniewicz. 250 1st ed. 2023. 264 1 Cham : |bSpringer International Publishing : |bImprint: Springer, |c2023. 300 1 online resource (421 pages) 336 text |btxt |2rdacontent 337 computer |bc |2rdamedia 338 online resource |bcr |2rdacarrier 490 1 Advances in Intelligent Systems and Computing, |x2194-5365 ; |v1433 504 Includes bibliographical references and index. 520 Nowadays, data analysis is becoming an appealing topic due to the emergence of new data types, dimensions, and sources. This motivates the development of probabilistic/statistical approaches and tools to cope with these data. Different communities of experts, namely statisticians, mathematicians, computer scientists, engineers, econometricians, and psychologists are more and more interested in facing this challenge. As a consequence, there is a clear need to build bridges between all these communities for Data Science. This book contains more than fifty selected recent contributions aiming to establish the above referred bridges. These contributions address very different and relevant aspects such as imprecise probabilities, information theory, random sets and random fuzzy sets, belief functions, possibility theory, dependence modelling and copulas, clustering, depth concepts, dimensionality reduction of complex data and robustness. 650 0 Engineering—Data processing. 650 0 Computational intelligence. 650 0 Artificial intelligence. 650 14 Data Engineering. 650 24 Computational Intelligence. 650 24 Artificial Intelligence. 776 08 |iPrint version:García-Escudero, Luis A. |tBuilding Bridges Between Soft and Statistical Methodologies for Data Science |dCham : Springer International Publishing AG,c2022 |z9783031155086 700 1 García-Escudero, Luis A., |eeditor. 830 0 Advances in Intelligent Systems and Computing, |x2194-5365 ; |v1433 906 BOOK