Description

Book Synopsis
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 treated and fuzzy information is retrievable.The book is suitable as a text for graduate courses in mathematics, computer science, and information science. It is also useful to researchers in the relevant area.

Table of Contents
Basic Knowledge on Classical Sets; Fuzzy Sets; Set Functions; Integrations; Information Fusion; Optimization and Soft Computing; Identification of Set Functions; Multiregressions Based on Nonlinear Integrals; Classifications Based on Nonlinear Integrals; Data Mining with Fuzzy Data.

Nonlinear Integrals And Their Applications In

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    A Hardback by Zhenyuan Wang, Rong Yang, Kwong-sak Leung

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      View other formats and editions of Nonlinear Integrals And Their Applications In by Zhenyuan Wang

      Publisher: World Scientific Publishing Co Pte Ltd
      Publication Date: 10/06/2010
      ISBN13: 9789812814678, 978-9812814678
      ISBN10: 9812814671

      Description

      Book Synopsis
      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 treated and fuzzy information is retrievable.The book is suitable as a text for graduate courses in mathematics, computer science, and information science. It is also useful to researchers in the relevant area.

      Table of Contents
      Basic Knowledge on Classical Sets; Fuzzy Sets; Set Functions; Integrations; Information Fusion; Optimization and Soft Computing; Identification of Set Functions; Multiregressions Based on Nonlinear Integrals; Classifications Based on Nonlinear Integrals; Data Mining with Fuzzy Data.

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