Handbook of research on big data clustering and machine learning

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"--

Библиографическая информация
Другие авторы: García Márquez, Fausto Pedro
Формат: Электронная книга
Язык:English
Публикация: Hershey, PA Engineering Science Reference (an imprint of IGI Global), [2020]
Серии:Advances in data mining and database management (ADMDM) book series.
Предметы:
Big data > Research > Handbooks, manuals, etc.
Cluster analysis > Research > Handbooks, manuals, etc.
Machine learning > Research > Handbooks, manuals, etc.
EBSCO eBooks
Handbooks and manuals.
Electronic books.
Online-ссылка:EBSCOhost
Перейти в каталог НБ ТГУ
Оглавление:
  • 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.

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