Titlebook: Learning from Data Streams in Dynamic Environments; Moamar Sayed-Mouchaweh Book 2016 The Author 2016 Adaptive Modeling.Data Streams.Drift

CT951

書目名稱Learning from Data Streams in Dynamic Environments影響因子(影響力)




書目名稱Learning from Data Streams in Dynamic Environments影響因子(影響力)學(xué)科排名




書目名稱Learning from Data Streams in Dynamic Environments網(wǎng)絡(luò)公開度




書目名稱Learning from Data Streams in Dynamic Environments網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Learning from Data Streams in Dynamic Environments被引頻次




書目名稱Learning from Data Streams in Dynamic Environments被引頻次學(xué)科排名




書目名稱Learning from Data Streams in Dynamic Environments年度引用




書目名稱Learning from Data Streams in Dynamic Environments年度引用學(xué)科排名




書目名稱Learning from Data Streams in Dynamic Environments讀者反饋




書目名稱Learning from Data Streams in Dynamic Environments讀者反饋學(xué)科排名

挖掘

格子架

2191-530X of learning in non-stationary environments, its interests, its applications and challenges and studies the complementarities and the links between the different methods and techniques of learning in evolving and non-stationary environments.978-3-319-25665-8978-3-319-25667-2Series ISSN 2191-530X Series E-ISSN 2191-5318

BRACE

Book 2016nments. It presents major and well-known methods and approaches for the design of systems able to learn and to fully adapt its structure and to adjust its parameters according to the changes in their environments. Also presents the problem of learning in non-stationary environments, its interests, i

放氣

Book 2016 its parameters according to the changes in their environments. Also presents the problem of learning in non-stationary environments, its interests, its applications and challenges and studies the complementarities and the links between the different methods and techniques of learning in evolving and non-stationary environments.

背叛者

mercenary

2191-530X ues in order to show their complementarities and to define sThis book addresses the problems of modeling, prediction, classification, data understanding and processing in non-stationary and unpredictable environments. It presents major and well-known methods and approaches for the design of systems

爆米花

Learning in Dynamic Environments,eristics of the concept drift are presented. Finally, the real-world applications generating drifting data streams are discussed. The goal is to give a picture of the problem of learning from data streams in dynamic environments, its causes, sources, and characteristics in order to discuss later alternatives to solve this problem.

etidronate

Moamar Sayed-MouchawehExamines the problem of learning in non-stationary environments, its interests, its applications and challenges.Compares methods and techniques in order to show their complementarities and to define s

完成

SpringerBriefs in Applied Sciences and Technologyhttp://image.papertrans.cn/l/image/582933.jpg