Stream Data Mining: Algorithms and Their Probabilistic Properties

Language: English

Published by Springer International Publishing, Springer Nature Switzerland Mär 2019, 2019

3030139611 / 9783030139612

Series: Book 50 of 95 - Studies in Big Data

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This item is printed on demand - Print on Demand Titel. Neuware -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 dealwith stream data, e.g. in telecommunication, banking, and sensor networks.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 340 pp. Englisch.

Seller Inventory # 9783030139612

Title
Stream Data Mining: Algorithms and Their Probabilistic Properties
Author
Leszek Rutkowski
Publisher
Springer International Publishing, Springer Nature Switzerland Mär 2019
Publication year
2019
Condition
Neu
Binding
Buch
Language
English
ISBN 10
3030139611
ISBN 13
9783030139612
Item weight
676 grams
Dimensions
241x160x24 mm
Series
Book 50 of 95: Studies in Big Data

buchversandmimpf2000

Emtmannsberg, BAYE, Germany

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AbeBooks seller since January 23, 2017

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