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Winner of the 2014 Technometrics Ziegel Prize for Outstanding Book
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. Addressing practical concerns extends beyond model fitting to topics such as handling class imbalance, selecting predictors, and pinpointing causes of poor model performance―all of which are problems that occur frequently in practice.
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. The data sets and corresponding code are available in the book’s companion AppliedPredictiveModeling R package, which is freely available on the CRAN archive.
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.
Readers and students interested in implementing the methods should have some basic knowledge of R. And a handful of the more advanced topics require some mathematical knowledge.
Publisher : Springer; 2013th edition (May 17, 2013)
Language : English
Hardcover : 613 pages
ISBN-10 : 1461468485
ISBN-13 : 978-1461468486
Item Weight : 22.9 pounds
Dimensions : 6.4 x 1.5 x 9.3 inches
Customers say
Customers find the book provides a very approachable, broad, yet just deep enough review of various concepts. They also say it’s a great book for learning data science and advanced techniques. Readers describe the writing quality as incredibly well-written without sacrificing technical explanation. They say the author is easy to follow and the text is easy to read. Customers also mention the value for money is well worth the price and the code quality is outstanding.
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