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[null,"1.","Record Nr.",null,"UNINA9910456219503321"]
[null,null,"Autore",null,"Wang Zhenyuan"]
[null,null,"Titolo",null,"Nonlinear integrals and their applications in data mining [[electronic resource] /] / Zhenyuan Wang, Rong Yang, Kwong-Sak Leung"]
[null,null,"Pubbl/distr/stampa",null,"Singapore ; ; Hackensack, N.J., : World Scientific, c2010"]
[null,null,"ISBN",null,"1-283-14352-6"]
[{"$nulls":4},"9786613143525"]
[{"$nulls":4},"981-281-468-X"]
[null,null,"Descrizione fisica",null,"1 online resource (360 p.)"]
[null,null,"Collana",null,"Advances in fuzzy systems : applications and theory ; ; v. 17 [i.e. 24]"]
[null,null,"Disciplina",null,"511.313"]
[null,null,"Soggetti",null,"Fuzzy sets"]
[{"$nulls":4},"Integrals"]
[{"$nulls":4},"Fuzzy logic"]
[{"$nulls":4},"Data mining"]
[{"$nulls":4},"Electronic books."]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Preface; Contents; List of Tables; List of Figures; Chapter 1: Introduction; Chapter 2: Basic Knowledge on Classical Sets; Chapter 3: Fuzzy Sets; Chapter 4: Set Functions; Chapter 5: Integrations; Chapter 6: Information Fusion; Chapter 7: Optimization and Soft Computing; Chapter 8: Identification of Set Functions; Chapter 9: Multiregression Based on Nonlinear Integrals; Chapter 10: Classifications Based on Nonlinear Integrals; Chapter 11: Data Mining with Fuzzy Data; Bibliography; Index"]
[null,null,null,"Sommario/riassunto","Regarding the set of all feature attributes in a given database as the universal set, this monograph discusses various nonadditive set functions that describe the interaction among the contributions from feature attributes towards a considered target attribute. Then, the relevant nonlinear integrals are investigated. These integrals can be applied as aggregation tools in information fusion and data mining, such as synthetic evaluation, nonlinear multiregressions, and nonlinear classifications. Some methods of fuzzification are also introduced for nonlinear integrals such that fuzzy data can be"]