是一本介绍预测模型的书籍，，发内容非常详尽，值得推荐给大家看

model predictive control,E.F.Camacho C.Bordons, 一本经典的预测控制英文书

Predictive Modeling with SAS Enterprise Miner: Practical Solutions for Business Applications, Second Edition。 Learn how to produce predictive models and prepare presentation-quality graphics in record time with Predictive Modeling with SAS Enterprise Miner: Practical Solutions for Business Applications, Second Edition. If you are a graduate student, researcher, or statistician interested in predictive modeling; a data mining expert who wants to learn SAS Enterprise Miner; or a business analyst looking for an introduction to predictive modeling using SAS Enterprise Miner, you'll be able to develop predictive models quickly and effectively using the theory and examples presented in this book. Author Kattamuri Sarma offers the theory behind, programming steps for, and examples of predictive modeling with SAS Enterprise Miner, along with exercises at the end of each chapter. You'll gain a comprehensive awareness of how to find solutions for your business needs. This second edition features expanded coverage of the SAS Enterprise Miner nodes, now including File Import, Time Series, Variable Clustering, Cluster, Interactive Binning, Principal Components, AutoNeural, DMNeural, Dmine Regression, Gradient Boosting, Ensemble, and Text Mining. Develop predictive models quickly, learn how to test numerous models and compare the results, gain an in-depth understanding of predictive models and multivariate methods, and discover how to do in-depth analysis. Do it all with Predictive Modeling with SAS Enterprise Miner.

This in-depth guide provides managers with a solid understanding of data and data trends, the opportunities that it can offer to businesses, and the dangers of these technologies. Written in an accessible style, Steven Finlay provides a contextual roadmap for developing solutions that deliver benefits to organizations. Table of Contents Chapter 1 Introduction Chapter 2 Using Predictive Models Chapter 3 Analytics, Organization And Culture Chapter 4 The Value Of Data Chapter 5 Ethics And Legislation Chapter 6 Types Of Predictive Models Chapter 7 The Predictive Analytics Process Chapter 8 How To Build A Predictive Model Chapter 9 Text Mining And Social Network Analysis Chapter 10 Hardware, Software And All That Jazz Appendix A. Glossary of Terms Appendix B. Further Sources of Information Appendix C. Lift Charts and Gain Charts