Predictive Modeling With Sas Enterprise Miner


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Predictive Modeling with SAS Enterprise Miner


Predictive Modeling with SAS Enterprise Miner

Author: Kattamuri S. Sarma

language: en

Publisher:

Release Date: 2013-12


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Learn the theory behind and methods for predictive modeling using SAS Enterprise Miner. 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 book is part of the SAS Press program.

Applying Predictive Analytics


Applying Predictive Analytics

Author: Richard V. McCarthy

language: en

Publisher: Springer

Release Date: 2019-03-12


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This textbook presents a practical approach to predictive analytics for classroom learning. It focuses on using analytics to solve business problems and compares several different modeling techniques, all explained from examples using the SAS Enterprise Miner software. The authors demystify complex algorithms to show how they can be utilized and explained within the context of enhancing business opportunities. Each chapter includes an opening vignette that provides real-life example of how business analytics have been used in various aspects of organizations to solve issue or improve their results. A running case provides an example of a how to build and analyze a complex analytics model and utilize it to predict future outcomes.

Predictive Modeling with SAS Enterprise Miner


Predictive Modeling with SAS Enterprise Miner

Author: Kattamuri S. Sarma

language: en

Publisher: SAS Institute

Release Date: 2017-07-20


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« Written for business analysts, data scientists, statisticians, students, predictive modelers, and data miners, this comprehensive text provides examples that will strengthen your understanding of the essential concepts and methods of predictive modeling. »--