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Applied Predictive Modeling

Amazon.com Price:  $60.72 (as of 05/05/2019 15:04 PST- Details)

Description

Winner of the 2014 Technometrics Ziegel Prize for Outstanding Book

Applied Predictive Modeling covers the overall predictive modeling process, beginning with the a very powerful steps of data preprocessing, data splitting and foundations of model tuning.  The text then provides intuitive explanations of a lot of common and modern regression and classification techniques, all the time 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 often in practice.
 
The text illustrates all parts of the modeling process through many hands-on, real-life examples.  And every chapter accommodates extensive R code for every step of the process.  The data sets and corresponding code are to be had in the book’s companion AppliedPredictiveModeling R package, which is freely to be had on the CRAN archive.
 
This multi-purpose text can be utilized 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, every chapter accommodates problem sets to help solidify the covered concepts and uses data to be had in the book’s R package.
 
Readers and students interested in implementing the methods will have to have some basic knowledge of R.  And a handful of the more advanced topics require some mathematical knowledge.


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