Description
Applied Predictive Modeling, 1st ed. 2013, Corr. 2nd printing 2018
Authors: Kuhn Max, Johnson Kjell
Language: EnglishSubject for Applied Predictive Modeling:
Keywords
Model; Non-Linear; Predictive Models; R; Regression Models; Regression Trees
Approximative price 63.29 €
In Print (Delivery period: 15 days).
Add to cart the print on demand of Kuhn Max, Johnson KjellPublication date: 03-2019
Support: Print on demand
Publication date: 03-2018
600 p. · 15.5x23.5 cm · Hardback
Description
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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.General Strategies.- Regression Models.- Classification Models.- Other Considerations.- Appendix.- References.- Indices.
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.
Book specializes in data analysis with focus on practice of predictive modeling
Useful as a guide for practitioners
Reader can reproduce all results using R
Includes supplementary material: sn.pub/extras