Computational business analytics - Das, Subrata Kumar (Boca Raton : CRC Press, Taylor & Francis Group, 2014)
Chapter 1. Analytics background and architectures -- chapter 2. Mathematical and statistical preliminaries -- chapter 3. Statistics for descriptive analytics -- chapter 4. Bayesian probability and inference -- chapter 5. Inferential statistics and predictive analytics -- chapter 6. Artificial intelligence for symbolic analytics -- chapter 7. Probabilistic graphical modeling -- chapter 8. Decision support and prescriptive analytics -- chapter 9. Time series modeling and forecasting -- chapter 10. Monte Carlo simulation -- chapter 11. Cluster analysis and segmentation -- chapter 12. Machine learning for analytics models -- chapter 13. Unstructured data and text analytics -- chapter 14. Semantic web -- chapter 15. Analytics tools -- chapter 16. Analytics case studies.
Includes bibliographical references (pages 463-477) and index.
CSE
Trim Education
Keywords: Business intelligence -- Data processing; Strategic planning -- Data processing; Business -- Computer programs; Business requirements analysis; Computer science