Title
Predictive Modeling With Sas Enterprise Miner: Practical Solutions For Business Applications, Third Edition,Used
Delivery time: 8-12 business days (International)
A stepbystep guide to predictive modeling!Kattamuri Sarma's Predictive Modeling with SAS Enterprise Miner: Practical Solutions for Business Applications, Third Edition, will show you how to develop and test predictive models quickly using SAS Enterprise Miner. Using realistic data, the book explains complex methods in a simple and practical way to readers from different backgrounds and industries. Incorporating the latest version of Enterprise Miner, this third edition also expands the section on time series.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. Topics covered include logistic regression, regression, decision trees, neural networks, variable clustering, observation clustering, data imputation, binning, data exploration, variable selection, variable transformation, and much more, including analysis of textual data.Develop predictive models quickly, learn how to test numerous models and compare the results, gain an indepth understanding of predictive models and multivariate methods, and discover how to do indepth analysis. Do it all with Predictive Modeling with SAS Enterprise Miner!
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We ship your order within 2–3 business days for USA deliveries and 5–8 business days for international shipments. Once your package has been dispatched from our warehouse, you'll receive an email confirmation with a tracking number, allowing you to track the status of your delivery.
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To facilitate a smooth return process, a Return Authorization (RA) Number is required for all returns. Returns without a valid RA number will be declined and may incur additional fees. You can request an RA number within 15 days of the original delivery date. For more details, please refer to our Return & Refund Policy page.
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Warranty
We provide a 2-year limited warranty, from the date of purchase for all our products.
If you believe you have received a defective product, or are experiencing any problems with your product, please contact us.
This warranty strictly does not cover damages that arose from negligence, misuse, wear and tear, or not in accordance with product instructions (dropping the product, etc.).
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Frequently Asked Questions
- Q: What is the main focus of 'Predictive Modeling with SAS Enterprise Miner'? A: The book primarily focuses on teaching readers how to develop and test predictive models using SAS Enterprise Miner, with practical solutions applicable to business scenarios.
- Q: Who is the intended audience for this book? A: The book is designed for business analysts, data scientists, statisticians, students, predictive modelers, and data miners, making it suitable for anyone looking to enhance their predictive modeling skills.
- Q: What topics are covered in this book? A: Topics include logistic regression, decision trees, neural networks, variable clustering, data imputation, data exploration, variable selection, and analysis of textual data, among others.
- Q: Is this book suitable for beginners in predictive modeling? A: Yes, the book explains complex methods in a simple and practical way, making it accessible to readers from various backgrounds and levels of experience.
- Q: What edition of the book is this, and what are its updates? A: This is the third edition, which incorporates the latest version of SAS Enterprise Miner and expands on time series analysis.
- Q: How many pages does the book contain? A: The book contains a total of 574 pages.
- Q: What is the binding type of this book? A: The book is bound in hardcover, providing durability and a professional appearance.
- Q: When was 'Predictive Modeling with SAS Enterprise Miner' published? A: The book was published on July 20, 2018.
- Q: What skills can I expect to gain from reading this book? A: Readers can expect to develop skills in creating and testing predictive models, understanding multivariate methods, and performing in-depth data analysis.
- Q: Who is the author of this book? A: The author of the book is Kattamuri Sarma, PhD.