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- Used
Seller: SustainableBooks.com, Amherst, NY, U.S.A.SustainableBooks.com
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Book is in Used-VeryGood condition. Pages and cover are clean and intact. Used items may not include supplementary materials such as CDs or access codes. May show signs of minor shelf wear and contain very limited notes and highlighting.
Seller Inventory # 1461468485-2-3
- Title
- Applied Predictive Modeling
- Author
- Kuhn, Max; Johnson, Kjell
- Publisher
- Springer
- Publication year
- 2013
- Condition
- Very Good
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 1461468485
- ISBN 13
- 9781461468486
- Edition
- 2nd Edition
- Item weight
- 2.25 pounds
Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. The text illustrates all parts of the modeling process through many hands-on, real-life examples, and every chapter contains extensive R code for each step of the process.
This multi-purpose text can be used as an introduction to predictive models and the overall modeling process, a practitioner’s reference handbook, or as a text for advanced undergraduate or graduate level predictive modeling courses. To that end, each chapter contains problem sets to help solidify the covered concepts and uses data available in the book’s R package."Synopsis" may belong to another edition of this title.
About the Author
Dr. Kuhn is a Director of Non-Clinical Statistics at Pfizer Global R&D in Groton Connecticut. He has been applying predictive models in the pharmaceutical and diagnostic industries for over 15 years and is the author of a number of R packages.
Dr. Johnson has more than a decade of statistical consulting and predictive modeling experience in pharmaceutical research and development. He is a co-founder of Arbor Analytics, a firm specializing in predictive modeling and is a former Director of Statistics at Pfizer Global R&D. His scholarly work centers on the application and development of statistical methodology and learning algorithms.
"About the title" may belong to another edition of this title.
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