Handbook of research on big data clustering and machine learning

"This book examines the relationship between the analytic principles of clustering and machine learning to big data. It also explores the connection between engineering/technology and the organizational, administrative, and planning abilities of management"--

Bibliographic Details
Other Authors: García Márquez, Fausto Pedro
Format: eBook
Language:English
Published: Hershey, PA Engineering Science Reference (an imprint of IGI Global), [2020]
Series:Advances in data mining and database management (ADMDM) book series.
Subjects:
Online Access:EBSCOhost
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020 |a 1799801071  |q (electronic book) 
020 |a 9781799801078  |q (electronic bk.) 
020 |z 9781799801061  |q (hardcover) 
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049 |a MAIN 
245 0 0 |a Handbook of research on big data clustering and machine learning  |c [edited by] Fausto Pedro Garcia Marquez. 
264 1 |a Hershey, PA  |b Engineering Science Reference (an imprint of IGI Global),  |c [2020] 
300 |a 1 online resource (xxi, 478 pages) 
490 1 |a Advances in data mining and database management (ADMDM) book series 
504 |a Includes bibliographical references and index. 
505 0 |a Chapter 1. Big data and clustering techniques -- Chapter 2. Big data analytics and models -- Chapter 3. Technologies for handling big data -- Chapter 4. Clustering and bayesian networks -- Chapter 5. Analysis of gravitation-based optimization algorithms for clustering and classification -- Chapter 6. Analytics and technology for practical forecasting -- Chapter 7. Modern statistical modeling in machine learning and big data analytics: statistical models for continuous and categorical variables -- Chapter 8. Enhanced logistic regression (ELR) model for big data -- Chapter 9. On foundations of estimation for nonparametric regression with continuous optimization -- Chapter 10. An overview of methodologies and challenges in sentiment analysis on social networks -- Chapter 11. Evaluation of optimum and coherent economic-capital portfolios under complex market prospects -- Chapter 12. Data-driven stochastic optimization for transportation road network design under uncertainty -- Chapter 13. Examining visitors' characteristics and behaviors in tourist destinations through mobile phone users' location data -- Chapter 14. Machine learning for smart tourism and retail -- Chapter 15. Predictive analysis of robotic manipulators through inertial sensors and pattern recognition -- Chapter 16. Call masking: a worrisome trend in Nigeria's telecommunications industry -- Chapter 17. An optimized three-dimensional clustering for microarray data -- Chapter 18. Identifying patterns in fresh produce purchases: the application of machine learning techniques -- Chapter 19. Urban spatial data computing: integration of GIS and GPS towards location-based recommendations. 
520 |a "This book examines the relationship between the analytic principles of clustering and machine learning to big data. It also explores the connection between engineering/technology and the organizational, administrative, and planning abilities of management"--  |c Provided by publisher. 
588 |a Description based on online resource; title from digital title page (viewed on November 27, 2019). 
653 0 |a Big data  |x Research  |v Handbooks, manuals, etc. 
653 0 |a Cluster analysis  |x Research  |v Handbooks, manuals, etc. 
653 0 |a Machine learning  |x Research  |v Handbooks, manuals, etc. 
655 0 |a EBSCO eBooks  |9 905790 
655 7 |a Handbooks and manuals.  |2 fast  |0 (OCoLC)fst01423877  |9 900333 
655 4 |a Electronic books.  |9 899821 
700 1 |a García Márquez, Fausto Pedro,  |9 462815 
710 2 |a IGI Global,  |e publisher.  |9 899844 
830 0 |a Advances in data mining and database management (ADMDM) book series.  |9 910005 
856 4 0 |3 EBSCOhost  |u https://www.lib.tsu.ru/limit/2023/EBSCO/2291122.pdf 
856 |y Перейти в каталог НБ ТГУ  |u https://koha.lib.tsu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=1013255 
910 |a EBSCO eBooks 
999 |c 1013255  |d 1013255 
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