عنوان

Learning from data streams in evolving environments :

شابک

3319898035

شابک

9783319898032

شابک اشتباه

3319898027

شابک اشتباه

9783319898025

عنوان اصلي

Learning from data streams in evolving environments :

نام عام مواد

[Book]

ساير اطلاعات عنواني

methods and applications /

نام نخستين پديدآور

Moamar Sayed-Mouchaweh, editor.

محل نشرو پخش و غیره

Cham, Switzerland :

نام ناشر، پخش کننده و غيره

Springer,

تاریخ نشرو بخش و غیره

[2019]

نام خاص و کميت اثر

1 online resource

عنوان فروست

Studies in big data ;

مشخصه جلد

volume 41

متن يادداشت

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.

بدون عنوان

0

متن يادداشت

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.

منبع سفارش / آدرس اشتراک

Springer Nature

شماره انبار

com.springer.onix.9783319898032

عنوان

Learning from data streams in evolving environments.

شماره استاندارد بين المللي کتاب و موسيقي

9783319898025

موضوع مستند نشده

Big data.

موضوع مستند نشده

Machine learning.

موضوع مستند نشده

Automatic control engineering.

موضوع مستند نشده

Big data.

موضوع مستند نشده

Communications engineering-- telecommunications.

موضوع مستند نشده

COMPUTERS-- General.

موضوع مستند نشده

Data mining.

موضوع مستند نشده

Machine learning.

موضوع مستند نشده

Reliability engineering.

موضوع مستند نشده

COM-- 000000

موضوع مستند نشده

TJK

شماره

ويراست

شماره رده

مستند نام اشخاص تاييد نشده

Sayed-Mouchaweh, Moamar

تاريخ عمليات

20200823114832.0

قواعد فهرست نويسي ( بخش توصيفي )

pn

نام الکترونيکي

نوع ماده

[Book]

تكميل شده

Y