Composition Operator for Credal Sets Reconsidered
This paper is the second attempt to introduce the composition operator, already known from probability, possibility, evidence and valuation-based systems theories, also for credal sets. We try to avoid the discontinuity which was present in the original d
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Maria Brigida Ferraro Paolo Giordani Barbara Vantaggi Marek Gagolewski María Ángeles Gil Przemysław Grzegorzewski Olgierd Hryniewicz Editors
Soft Methods for Data Science
Advances in Intelligent Systems and Computing Volume 456
Series editor Janusz Kacprzyk, Polish Academy of Sciences, Warsaw, Poland e-mail: [email protected]
About this Series The series “Advances in Intelligent Systems and Computing” contains publications on theory, applications, and design methods of Intelligent Systems and Intelligent Computing. Virtually all disciplines such as engineering, natural sciences, computer and information science, ICT, economics, business, e-commerce, environment, healthcare, life science are covered. The list of topics spans all the areas of modern intelligent systems and computing. The publications within “Advances in Intelligent Systems and Computing” are primarily textbooks and proceedings of important conferences, symposia and congresses. They cover significant recent developments in the field, both of a foundational and applicable character. An important characteristic feature of the series is the short publication time and world-wide distribution. This permits a rapid and broad dissemination of research results.
Advisory Board Chairman Nikhil R. Pal, Indian Statistical Institute, Kolkata, India e-mail: [email protected] Members Rafael Bello, Universidad Central “Marta Abreu” de Las Villas, Santa Clara, Cuba e-mail: [email protected] Emilio S. Corchado, University of Salamanca, Salamanca, Spain e-mail: [email protected] Hani Hagras, University of Essex, Colchester, UK e-mail: [email protected] László T. Kóczy, Széchenyi István University, Győr, Hungary e-mail: [email protected] Vladik Kreinovich, University of Texas at El Paso, El Paso, USA e-mail: [email protected] Chin-Teng Lin, National Chiao Tung University, Hsinchu, Taiwan e-mail: [email protected] Jie Lu, University of Technology, Sydney, Australia e-mail: [email protected] Patricia Melin, Tijuana Institute of Technology, Tijuana, Mexico e-mail: [email protected] Nadia Nedjah, State University of Rio de Janeiro, Rio de Janeiro, Brazil e-mail: [email protected] Ngoc Thanh Nguyen, Wroclaw University of Technology, Wroclaw, Poland e-mail: [email protected] Jun Wang, The Chinese University of Hong Kong, Shatin, Hong Kong e-mail: [email protected]
More information about this series at http://www.springer.com/series/11156
Maria Brigida Ferraro Paolo Giordani Barbara Vantaggi Marek Gagolewski María Ángeles Gil Przemysław Grzegorzewski Olgierd Hryniewicz •
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Editors
Soft Methods for Data Science
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Editors Maria Brigida Ferraro Department of Statistical Sciences Sapienza University of Rome Rome Italy Paolo Giordani Department of Statistical Sciences Sapienza University of Rome Rome Italy Barbara Vantaggi Department of Basic and Applied Sciences for Engineering Sapienza University of Rome Rome Italy Marek Gagolewski Department of Stochastic Methods, Systems Research Institute Polish Academy of Sciences Warsaw Poland
María
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