Studies in Big Data

Stream Data Mining: Algorithms and Their Probabilistic Properties

Authors: Rutkowski, Leszek, Jaworski, Maciej, Duda, Piotr

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  • Presents a unique and innovative approach to stream data mining
  • Unlike the vast majority of previous approaches, which are largely based on heuristics, it highlights methods and algorithms that are mathematically justified
  • Is intended for a professional audience composed of researchers and practitioners who deal with stream data (e.g. in telecommunication, banking, and sensor networks)
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eBook $89.00
price for USA in USD (gross)
  • ISBN 978-3-030-13962-9
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  • Immediate eBook download after purchase
Hardcover $169.99
price for USA in USD
  • ISBN 978-3-030-13961-2
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

This book presents a unique approach to stream data mining. Unlike the vast majority of previous approaches, which are largely based on heuristics, it highlights methods and algorithms that are mathematically justified. First, it describes how to adapt static decision trees to accommodate data streams; in this regard, new splitting criteria are developed to guarantee that they are asymptotically equivalent to the classical batch tree. Moreover, new decision trees are designed, leading to the original concept of hybrid trees. In turn, nonparametric techniques based on Parzen kernels and orthogonal series are employed to address concept drift in the problem of non-stationary regressions and classification in a time-varying environment. Lastly, an extremely challenging problem that involves designing ensembles and automatically choosing their sizes is described and solved. Given its scope, the book is intended for a professional audience of researchers and practitioners who deal with stream data, e.g. in telecommunication, banking, and sensor networks.

Table of contents (15 chapters)

Table of contents (15 chapters)

Buy this book

eBook $89.00
price for USA in USD (gross)
  • ISBN 978-3-030-13962-9
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $169.99
price for USA in USD
  • ISBN 978-3-030-13961-2
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Stream Data Mining: Algorithms and Their Probabilistic Properties
Authors
Series Title
Studies in Big Data
Series Volume
56
Copyright
2020
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
eBook ISBN
978-3-030-13962-9
DOI
10.1007/978-3-030-13962-9
Hardcover ISBN
978-3-030-13961-2
Series ISSN
2197-6503
Edition Number
1
Number of Pages
IX, 330
Number of Illustrations
48 b/w illustrations, 63 illustrations in colour
Topics