Stream Data Mining: Algorithms And Their Probabilistic Properties - Rutkowski Leszek; Jaworski Maciej; Duda Piotr | Libro Springer 03/2019 - HOEPLI.it


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rutkowski leszek; jaworski maciej; duda piotr - stream data mining: algorithms and their probabilistic properties

Stream Data Mining: Algorithms and Their Probabilistic Properties

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Dettagli

Genere:Libro
Lingua: Inglese
Editore:

Springer

Pubblicazione: 03/2019
Edizione: 1st ed. 2020





Sommario

Introduction and Overview of the Main Results of the Book.- Basic concepts of data stream mining.-  Decision Trees in Data Stream Mining.-  Splitting Criteria based on the McDiarmid’s Theorem.




Trama

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.








Altre Informazioni

ISBN:

9783030139612

Condizione: Nuovo
Collana: Studies in Big Data
Dimensioni: 235 x 155 mm Ø 676 gr
Formato: Copertina rigida
Illustration Notes:48 Illustrations, black and white
Pagine Arabe: 330
Pagine Romane: ix






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