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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