عنوان

Applied predictive modeling /

شابک

1461468493

شابک

9781461468493

شابک اشتباه

1461468485

شابک اشتباه

9781461468486

شماره

b623689

عنوان اصلي

Applied predictive modeling /

نام عام مواد

[Book]

نام نخستين پديدآور

Max Kuhn, Kjell Johnson.

نام خاص و کميت اثر

1 online resource (xiii, 600 pages) :

ساير جزييات

illustrations (some color)

متن يادداشت

Includes bibliographical references and index.

متن يادداشت

This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics. 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. 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.

منبع سفارش / آدرس اشتراک

OverDrive, Inc.

شماره انبار

792A51F1-6BFD-42A2-AFF7-035AC0934EBB

عنوان

Applied predictive modeling.

شماره استاندارد بين المللي کتاب و موسيقي

9781461468486

موضوع مستند نشده

Mathematical models.

موضوع مستند نشده

Mathematical statistics.

موضوع مستند نشده

Prediction theory.

موضوع مستند نشده

Statistics as Topic.

موضوع مستند نشده

Mathematical models.

موضوع مستند نشده

Mathematical statistics.

موضوع مستند نشده

Prediction theory.

موضوع مستند نشده

MBNS

موضوع مستند نشده

MED090000

موضوع مستند نشده

PBT

شماره

ويراست

شماره رده

نشانه اثر

مستند نام اشخاص تاييد نشده

Kuhn, Max

مستند نام اشخاص تاييد نشده

Johnson, Kjell

تاريخ عمليات

20201221082807.0

قواعد فهرست نويسي ( بخش توصيفي )

pn

نام الکترونيکي

نوع ماده

[Book]

کد کاربرگه

270410

تكميل شده

Y