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Max Kuhn - Applied Predictive Modeling - 9781461468486 - V9781461468486
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Applied Predictive Modeling

€ 114.47
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Description for Applied Predictive Modeling Hardback. This book provides an introduction to predictive models as well as a guide to applying them. It will serve as a useful guide for practitioners. All results can be reproduced using R. Num Pages: 600 pages, 50 black & white illustrations, 153 colour illustrations, 10 black & white tables, biogra. BIC Classification: PBT; UFM. Category: (P) Professional & Vocational. Dimension: 243 x 162 x 38. Weight in Grams: 1010.

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 ... Read more

Product Details

Publisher
Springer-Verlag New York Inc. United States
Number of pages
620
Format
Hardback
Publication date
2018
Condition
New
Weight
1044g
Number of Pages
600
Place of Publication
New York, NY, United States
ISBN
9781461468486
SKU
V9781461468486
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15

About Max Kuhn
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 ... Read more

Reviews for Applied Predictive Modeling
“…In teaching a data science course…I use a range of different resources because I need to cover working with data, model evaluation, and machine learning methods. The next time I teach this course, I will use only this book because it covers all of these aspects of the field.” (Louis Luangkesorn, lugerpitt.blogspot.com, June 2015) “There are ... Read more

Goodreads reviews for Applied Predictive Modeling


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