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Learning from Data Streams in Evolving Environments = Methods and Applications /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Learning from Data Streams in Evolving Environments/ edited by Moamar Sayed-Mouchaweh.
其他題名:	Methods and Applications /
其他作者:	Sayed-Mouchaweh, Moamar.
面頁冊數:	VIII, 317 p. 131 illus., 95 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Electrical engineering. -
電子資源:	https://doi.org/10.1007/978-3-319-89803-2
ISBN:	9783319898032

Learning from Data Streams in Evolving Environments = Methods and Applications /
Learning from Data Streams in Evolving EnvironmentsMethods and Applications /[electronic resource] :edited by Moamar Sayed-Mouchaweh. - 1st ed. 2019. - VIII, 317 p. 131 illus., 95 illus. in color.online resource. - Studies in Big Data,412197-6503 ;. - Studies in Big Data,8.

Chapter1: Transfer Learning in Non-Stationary Environments -- Chapter2: A new combination of diversity techniques in ensemble classifiers for handling complex concept drift -- Chapter3: Analyzing and Clustering Pareto-Optimal Objects in Data Streams -- Chapter4: Error-bounded Approximation of Data Stream: Methods and Theories -- Chapter5: Ensemble Dynamics in Non-stationary Data Stream Classification -- Chapter6: Processing Evolving Social Networks for Change Detection based on Centrality Measures -- Chapter7: Large-scale Learning from Data Streams with Apache SAMOA -- Chapter8: Process Mining for Analyzing Customer Relationship Management Systems A Case Study -- Chapter9: Detecting Smooth Cluster Changes in Evolving Graph Sequences -- Chapter10: Efficient Estimation of Dynamic Density Functions with Applications in Data Streams -- Chapter11: A Survey of Methods of Incremental Support Vector Machine Learning -- Chapter12: On Social Network-based Algorithms for Data Stream Clustering.

This edited book covers recent advances of techniques, methods and tools treating the problem of learning from data streams generated by evolving non-stationary processes. The goal is to discuss and overview the advanced techniques, methods and tools that are dedicated to manage, exploit and interpret data streams in non-stationary environments. The book includes the required notions, definitions, and background to understand the problem of learning from data streams in non-stationary environments and synthesizes the state-of-the-art in the domain, discussing advanced aspects and concepts and presenting open problems and future challenges in this field. Provides multiple examples to facilitate the understanding data streams in non-stationary environments; Presents several application cases to show how the methods solve different real world problems; Discusses the links between methods to help stimulate new research and application directions.

ISBN: 9783319898032

Standard No.: 10.1007/978-3-319-89803-2doiSubjects--Topical Terms:

596380
Electrical engineering.

LC Class. No.: TK1-9971

Dewey Class. No.: 621.382

Learning from Data Streams in Evolving Environments = Methods and Applications /
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