Machine Learning for Data Streams: with Practical Examples in MOA by Albert Bife

Description: Machine Learning for Data Streams by Albert Bifet, Ricard Gavalda, Geoffrey Holmes, Bernhard Pfahringer Estimated delivery 3-12 business days Format Paperback Condition Brand New 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.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. Author Biography Albert Bifet is Professor of Computer Science at Telecom ParisTech.Ricard Gavald is Professor of Computer Science at the Polit cnica de Catalunya, Barcelona.Geoff Holmes is Professor and Dean of Computing at the University of Waikato in Hamilton, New Zealand.Bernhard Pfahringer is Professor of Computer Science at the University of Auckland, New Zealand. Details ISBN 026254783X ISBN-13 9780262547833 Title Machine Learning for Data Streams Author Albert Bifet, Ricard Gavalda, Geoffrey Holmes, Bernhard Pfahringer Format Paperback Year 2023 Pages 288 Publisher MIT Press Ltd GE_Item_ID:141779148; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. Returns If you wish to return an item, please consult our Returns Policy as below: Please contact Customer Services and request "Return Authorisation" before you send your item back to us. Unauthorised returns will not be accepted. Returns must be postmarked within 4 business days of authorisation and must be in resellable condition. Returns are shipped at the customer's risk. We cannot take responsibility for items which are lost or damaged in transit. For purchases where a shipping charge was paid, there will be no refund of the original shipping charge. Additional Questions If you have any questions please feel free to Contact Us. Categories Baby Books Electronics Fashion Games Health & Beauty Home, Garden & Pets Movies Music Sports & Outdoors Toys

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