Applied Predictive Modeling
Applied Predictive Modeling
Winner of the 2014 Technometrics Ziegel Prize for Outstanding BookApplied 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.
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From the Back Cover
About the Author
Kjell Johnson, Ph.D, has over 15 years of predictive modeling and statistical consulting experience in pharmaceutical research and development and other industries. He is a former Director of Statistics at Pfizer R&D, and is a co-founder of Arbor Analytics, a firm that specializes in predictive modeling and statistical consulting and currently serves the pharmaceutical, medical devices, finance, and insurance industries. His scholarly work centers on the application and development of statistical methodology and learning algorithms.
Drs. Kuhn and Johnson have taught numerous short-courses on predictive modeling for organizations such as useR!, Predictive Analytics World, Eastern North American Region, American Chemical Society, Society for Biomolecular Screening, Deming Conference, and individual corporations.
“This strong, technical, hands-on treatment clearly spells out the concepts, and illustrates its themes tangibly with the language R, the most popular open source analytics solution.” (Eric Siegel, Ph.D. Founder, Predictive Analytics World, Author, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die)
–This text refers to the hardcover edition.
|Best Sellers Rank|
#509,887 in Kindle Store (See Top 100 in Kindle Store) #37 in Biostatistics (Kindle Store) #80 in Medical Research (Kindle Store) #84 in Mathematical & Statistical
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