General Strategies.- Regression Models.- Classification Models.- Other Considerations.- Appendix.- References.- Indices.
"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)
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.
“…In teaching a data science course…I use a range of different
resources because I need to cover working with data, model
evaluation, and machine learning methods. The next time I teach
this course, I will use only this book because it covers all of
these aspects of the field.” (Louis Luangkesorn,
lugerpitt.blogspot.com, June 2015)
“There are a wide variety of books available on predictive
analytics and data modeling around the web…we’ve carefully selected
the following 10 books, based on relevance, popularity, online
ratings, and their ability to add value to your business. 1.
Applied Predictive Modeling.” (Timothy King, Business Intelligence
Solutions Review, solutions-review.com, June 2015) "Applied
Predictive Modeling aims to expose many of these techniques in a
very readable and self-contained book. This is a very applied and
hands-on book. It guides the reader through many examples that
serve to illustrate main points, and it raises possible issues and
considerations that are oftentimes overlooked or not sufficiently
reflected upon. Highly recommended." (Bojan Tunguz,
tunguzreview.com, June 2015)“This monograph presents a very
friendly practical course on prediction techniques for regression
and classification models… It is a well-written book very useful to
students and practitioners who need an immediate and helpful way to
apply complex statistical techniques.” (Stan Lipovetsky,
Technometrics, Vol. 56 (3), August 2014)
“In my judgment, Applied Predictive Modeling by Max Kuhn
and Kjell Johnson (Springer 2013) ought to be at the very top of
the reading list …They come across like coaches who really, really
want you to be able to do this…Applied Predictive Modeling is
a remarkable text…it is the succinct distillation of years of
experience of two expert modelers…” (Joseph Rickert,
blog.revolutionanalytics.com, June 2014)
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