Noise Filtering for Big Data Analytics - Rilegato

 
9783110697094: Noise Filtering for Big Data Analytics
Rilegato
ISBN 10: 3110697092 ISBN 13: 9783110697094
Casa editrice: De Gruyter, 2022

Sinossi

This book explains how to perform data de-noising, in large scale, with a satisfactory level of accuracy. Three main issues are considered. Firstly, how to eliminate the error propagation from one stage to next stages while developing a filtered model. Secondly, how to maintain the positional importance of data whilst purifying it. Finally, preservation of memory in the data is crucial to extract smart data from noisy big data. If, after the application of any form of smoothing or filtering, the memory of the corresponding data changes heavily, then the final data may lose some important information. This may lead to wrong or erroneous conclusions. But, when anticipating any loss of information due to smoothing or filtering, one cannot avoid the process of denoising as on the other hand any kind of analysis of big data in the presence of noise can be misleading. So, the entire process demands very careful execution with efficient and smart models in order to effectively deal with it.

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Informazioni sull?autore

Souvik Bhattacharyya, Koushik Ghosh, University of Burdwan,West Bengal, India.

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Editore
De Gruyter
Data di pubblicazione
2022
Lingua
Inglese
ISBN 10 
3110697092
ISBN 13 
9783110697094
Rilegatura
Copertina rigida
Numero edizione
1
Numero di pagine
248
Redattore
Bhattacharyya Souvik, Ghosh Koushik
Contatto del produttore
Walter de Gruyter GmbH
info@degruyter.com

Genthiner Straße 13
Berlin
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Germania