Applied Predictive Modeling

📚📚 I. THÔNG TIN SẢN PHẨM
📒 Mã sản phẩm :  STT1010
📒 Nhà xuất bản : Springer; 2013th edition (May 17, 2013)
📒 Tác giả :   Max Kuhn, Kjell Johnson
📒 Ngôn ngữ :   Tiếng Anh
📒 ISBN      : 1461468485
📒 Số trang :  613  trang
📒 Hình thức : Bìa Mềm, in ĐEN TRẮNG
📒 Loại : Sách gia công đóng gáy keo chắc chắn chất lượng cao
📒 Giấy in : Giấy ngoại định lượng 70msg, viết vẽ và hightlight thoải mái.
📒 Chất lượng : Bản in rõ nét, giá rất tốt cho mọi người.

📚📚 II. MÔ TẢ SẢN PHẨM
📒 1.Mô tả sản phẩm

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.

📒 2. Tác giả

Max Kuhn, Ph.D., is a Senior Director in Research & Development at Pfizer in Groton, CT.  He has been applying predictive models in the pharmaceutical and diagnostic industries for over 15 years.   Dr. Kuhn has made many of contributions to statistical computing.  He is the author of eight R packages for techniques in machine learning (notably caret) and reproducible research and is an Associate Editor for the Journal of Statistical Software.

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.