Description: Machine Learning for Data Streams: with Practical Examples in MOA (Adaptive Computation and Machine Learning series) Bifet, Albert; Gavalda, Ricard; Holmes, Geoffrey and Pfahringer, Bernhard Product Overview 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. Read more Details Publisher : The MIT Press (March 2, 2018) Language : English Hardcover : 288 pages ISBN-10 : 0262037793 ISBN-13 : 92 Reading age : 18 years and up Grade level : 12 and up Item Weight : 1.58 pounds Dimensions : 9.1 x 7.2 x 1 inches Best Sellers Rank: #3,127,286 in Books (See Top 100 in Books) #909 in Artificial Intelligence (Books) #1,053 in Database Storage & Design #1,307 in Data Mining (Books) We have been selling used books since 2012, and we've learned that the most important thing is doing good business. Honesty is our policy. Free Shipping We ship worldwide. We have multiple warehouses around the world, so please note the extended handling time on certain listings.
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ISBN: 0262037793
ISBN10: 0262037793
ISBN13: 9780262037792
EAN: 9780262037792
MPN: does not apply
Brand: MIT Press
GTIN: 09780262037792
Number of Pages: 288 Pages
Publication Name: Machine Learning for Data Streams : with Practical Examples in Moa
Language: English
Publisher: MIT Press
Publication Year: 2018
Subject: Intelligence (Ai) & Semantics, Databases / Data Mining
Item Height: 0.9 in
Type: Textbook
Item Weight: 25.3 Oz
Subject Area: Computers
Item Length: 9.4 in
Author: Bernhard Pfahringer, Albert Bifet, Geoffrey Holmes, Ricard Gavalda
Series: Adaptive Computation and Machine Learning Ser.
Item Width: 7.2 in
Format: Hardcover
