This book is about predictive analytics. Yet each chapter could easily be handled by an entire volume of its own. So one might think of this a survey of predictive modeling. A predictive model is a statistical model or machine learning model used to predict future behavior based on past behavior. In order to use this book one should have a basic understanding of mathematical statistics - it is an advanced book. Some theoretical foundations are laid out but not proven but references are provided for additional coverage. Every chapter culminates in an example using R. R is a free software environment for statistical computing and graphics. You may download R from a preferred CRAN mirror at http://www.r-project.org/. The book is organized so that statistical models are presented first (hopefully in a logical order) followed by machine learning models and then applications: uplift modeling and time series. One could use this a textbook with problem solving in R-but there are no by-hand exercises.
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