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Learning from Data Streams

Learning from Data Streams PDF Author: João Gama
Publisher: Springer Science & Business Media
ISBN: 3540736786
Category : Computers
Languages : en
Pages : 243

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Book Description
Processing data streams has raised new research challenges over the last few years. This book provides the reader with a comprehensive overview of stream data processing, including famous prototype implementations like the Nile system and the TinyOS operating system. Applications in security, the natural sciences, and education are presented. The huge bibliography offers an excellent starting point for further reading and future research.

Learning from Data Streams

Learning from Data Streams PDF Author: João Gama
Publisher: Springer Science & Business Media
ISBN: 3540736786
Category : Computers
Languages : en
Pages : 243

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Book Description
Processing data streams has raised new research challenges over the last few years. This book provides the reader with a comprehensive overview of stream data processing, including famous prototype implementations like the Nile system and the TinyOS operating system. Applications in security, the natural sciences, and education are presented. The huge bibliography offers an excellent starting point for further reading and future research.

Learning from Data Streams in Evolving Environments

Learning from Data Streams in Evolving Environments PDF Author: Moamar Sayed-Mouchaweh
Publisher: Springer
ISBN: 3319898035
Category : Technology & Engineering
Languages : en
Pages : 317

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Book Description
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.

Learning from Data Streams in Dynamic Environments

Learning from Data Streams in Dynamic Environments PDF Author: Moamar Sayed-Mouchaweh
Publisher: Springer
ISBN: 331925667X
Category : Technology & Engineering
Languages : en
Pages : 75

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Book Description
This 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 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, 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.

Machine Learning for Data Streams

Machine Learning for Data Streams PDF Author: Albert Bifet
Publisher: MIT Press
ISBN: 0262037793
Category : Computers
Languages : en
Pages : 288

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Book Description
A hands-on approach to tasks and techniques in data stream mining and real-time analytics, with examples in MOA, a popular freely available open-source software framework. Today many information sources—including sensor networks, financial markets, social networks, and healthcare monitoring—are so-called data streams, arriving sequentially and at high speed. Analysis must take place in real time, with partial data and without the capacity to store the entire data set. This book presents algorithms and techniques used in data stream mining and real-time analytics. Taking a hands-on approach, the book demonstrates the techniques using MOA (Massive Online Analysis), a popular, freely available open-source software framework, allowing readers to try out the techniques after reading the explanations. The book first offers a brief introduction to the topic, covering big data mining, basic methodologies for mining data streams, and a simple example of MOA. More detailed discussions follow, with chapters on sketching techniques, change, classification, ensemble methods, regression, clustering, and frequent pattern mining. Most of these chapters include exercises, an MOA-based lab session, or both. Finally, the book discusses the MOA software, covering the MOA graphical user interface, the command line, use of its API, and the development of new methods within MOA. The book will be an essential reference for readers who want to use data stream mining as a tool, researchers in innovation or data stream mining, and programmers who want to create new algorithms for MOA.

Recent Trends in Learning From Data

Recent Trends in Learning From Data PDF Author: Luca Oneto
Publisher: Springer Nature
ISBN: 303043883X
Category : Technology & Engineering
Languages : en
Pages : 221

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Book Description
This book offers a timely snapshot and extensive practical and theoretical insights into the topic of learning from data. Based on the tutorials presented at the INNS Big Data and Deep Learning Conference, INNSBDDL2019, held on April 16-18, 2019, in Sestri Levante, Italy, the respective chapters cover advanced neural networks, deep architectures, and supervised and reinforcement machine learning models. They describe important theoretical concepts, presenting in detail all the necessary mathematical formalizations, and offer essential guidance on their use in current big data research.

Knowledge Discovery from Data Streams

Knowledge Discovery from Data Streams PDF Author: Joao Gama
Publisher: CRC Press
ISBN: 1439826129
Category : Business & Economics
Languages : en
Pages : 255

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Book Description
Since the beginning of the Internet age and the increased use of ubiquitous computing devices, the large volume and continuous flow of distributed data have imposed new constraints on the design of learning algorithms. Exploring how to extract knowledge structures from evolving and time-changing data, Knowledge Discovery from Data Streams presents a coherent overview of state-of-the-art research in learning from data streams. The book covers the fundamentals that are imperative to understanding data streams and describes important applications, such as TCP/IP traffic, GPS data, sensor networks, and customer click streams. It also addresses several challenges of data mining in the future, when stream mining will be at the core of many applications. These challenges involve designing useful and efficient data mining solutions applicable to real-world problems. In the appendix, the author includes examples of publicly available software and online data sets. This practical, up-to-date book focuses on the new requirements of the next generation of data mining. Although the concepts presented in the text are mainly about data streams, they also are valid for different areas of machine learning and data mining.

Learning from Data Streams

Learning from Data Streams PDF Author: João Gama
Publisher: Springer Science & Business Media
ISBN: 3540736794
Category : Computers
Languages : en
Pages : 244

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Book Description
Processing data streams has raised new research challenges over the last few years. This book provides the reader with a comprehensive overview of stream data processing, including famous prototype implementations like the Nile system and the TinyOS operating system. Applications in security, the natural sciences, and education are presented. The huge bibliography offers an excellent starting point for further reading and future research.

Learning from Data Streams with Randomized Forests

Learning from Data Streams with Randomized Forests PDF Author: T. Seah
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Book Description


STAIRS 2008

STAIRS 2008 PDF Author: Amedeo Cesta
Publisher: IOS Press
ISBN: 1586038931
Category : Computers
Languages : en
Pages : 213

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Book Description
Contains a series of papers selected from the peer-reviewing process for STAIRS-08: the fourth European Starting Artificial Intelligence Researcher Symposium, an international meeting intended for AI researchers from all countries, at the beginning of their career - PhD students or people holding a PhD for less than one year.

Encyclopedia of Data Warehousing and Mining, Second Edition

Encyclopedia of Data Warehousing and Mining, Second Edition PDF Author: Wang, John
Publisher: IGI Global
ISBN: 1605660116
Category : Computers
Languages : en
Pages : 2542

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Book Description
There are more than one billion documents on the Web, with the count continually rising at a pace of over one million new documents per day. As information increases, the motivation and interest in data warehousing and mining research and practice remains high in organizational interest. The Encyclopedia of Data Warehousing and Mining, Second Edition, offers thorough exposure to the issues of importance in the rapidly changing field of data warehousing and mining. This essential reference source informs decision makers, problem solvers, and data mining specialists in business, academia, government, and other settings with over 300 entries on theories, methodologies, functionalities, and applications.