Machine Learning for Data Streams

Machine Learning for Data Streams
Author :
Publisher : MIT Press
Total Pages : 289
Release :
ISBN-10 : 9780262547833
ISBN-13 : 026254783X
Rating : 4/5 (83X Downloads)

Book Synopsis Machine Learning for Data Streams by : Albert Bifet

Download or read book Machine Learning for Data Streams written by Albert Bifet and published by MIT Press. This book was released on 2023-05-09 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.


Machine Learning for Data Streams Related Books

Machine Learning for Data Streams
Language: en
Pages: 289
Authors: Albert Bifet
Categories: Computers
Type: BOOK - Published: 2023-05-09 - Publisher: MIT Press

DOWNLOAD EBOOK

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
Reliable Machine Learning
Language: en
Pages: 411
Authors: Cathy Chen
Categories: Computers
Type: BOOK - Published: 2021-10-12 - Publisher: "O'Reilly Media, Inc."

DOWNLOAD EBOOK

Whether you're part of a small startup or a multinational corporation, this practical book shows data scientists, software and site reliability engineers, produ
Learning in Non-Stationary Environments
Language: en
Pages: 439
Authors: Moamar Sayed-Mouchaweh
Categories: Technology & Engineering
Type: BOOK - Published: 2012-04-13 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

Recent decades have seen rapid advances in automatization processes, supported by modern machines and computers. The result is significant increases in system c
Neural Information Processing
Language: en
Pages: 532
Authors: Biao Luo
Categories: Neural computers
Type: BOOK - Published: 2024 - Publisher: Springer Nature

DOWNLOAD EBOOK

The nine-volume set constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, C
Machine Learning, Optimization, and Data Science
Language: en
Pages: 571
Authors: Giuseppe Nicosia
Categories: Computers
Type: BOOK - Published: 2022-02-01 - Publisher: Springer Nature

DOWNLOAD EBOOK

This two-volume set, LNCS 13163-13164, constitutes the refereed proceedings of the 7th International Conference on Machine Learning, Optimization, and Data Scie