This book is about predictive modeling. Yet, each chapter could easily be handled by an entire volume of its own. So one might think of this as a survey of predictive models, both statistical and machine learning. We define predictive modeling as a statistical model or machine learning model used to predict future behavior based on past behavior.
Predictive modeling and predictive analytics has often been used as synonyms. In recent years, that has been changing and predictive modeling is really as subset of analytics, which may also include descriptive and decision modeling. Of course it also encompasses the data mining and analysis that must be performed before and after.
In order to use this book, the reader should have a basic understanding of statistics (statistical inference, models, tests, etc.)—this is an advanced book. Every chapter culminates in an example using R. R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS.