Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/7543
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dc.contributor.authorWang, Zhenyuanen_US
dc.contributor.authorYang, Rongen_US
dc.contributor.authorProf. LEUNG Kwong Saken_US
dc.date.accessioned2023-03-23T03:44:10Z-
dc.date.available2023-03-23T03:44:10Z-
dc.date.issued2010-
dc.identifier.citationNonlinear Integrals and their Applications in Data Mining, 2010, pp. 1 - 340en_US
dc.identifier.isbn978-981281468-5-
dc.identifier.isbn9812814671-
dc.identifier.isbn978-981281467-8-
dc.identifier.urihttp://hdl.handle.net/20.500.11861/7543-
dc.description.abstractRegarding 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. © 2010 by World Scientific Publishing Co. Pte. Ltd. All rights reserved.en_US
dc.language.isoenen_US
dc.publisherWorld Scientific Publishing Co.en_US
dc.relation.ispartofNonlinear Integrals and their Applications in Data Miningen_US
dc.titleNonlinear integrals and their applications in data miningen_US
dc.typeBooken_US
dc.identifier.doi10.1142/6861-
item.fulltextNo Fulltext-
crisitem.author.deptDepartment of Applied Data Science-
Appears in Collections:Applied Data Science - Publication
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