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Thursday, September 26, 2013

Review: Modeling Techniques in Predictive Analytics

Modeling Techniques in Predictive Analytics: Business Problems and Solutions with R  by Thomas W. Miller 

This book does an excellent job of defining prediction, which I have rarely found done well  in a text.  The first chapter: Analytics and Data Science, in a relatively few pages, defines both the value of visualization and the methodology for getting and verifying a prediction.  Nicely and very simply and accessibly described.   The R code for this and every chapter can be found online here.  I have yet to use or test their code, but it seems very well documented.   This book does not teach R. I did not expect it to, ... but anyone who knows coding can follow along after getting an introduction.

Following chapters address specific areas of application:  Advertising and Promotion, Preference and Choice, Market Basket Analysis, Economic Data Analysis, Operations Management, Text Analytcs, Sentiment Analysis, Sports Analytics and Spatial Analysis.  Each of these topics contain a number of foundation problems, and a book of this type cannot cover them all, but the examples used are reasonable starting examples.

I have read the introductions of several of these topics, and the explanations are well done.  Code is printed on pages. and is often long and somewhat hard to read.  I will probably follow it on the online forms.

The text is heavily footnoted.   I like that, but the having the footnotes in the text make it somewhat harder to scan, would have preferred them in the index.

The Appendix contains description of a number of R language packs to support work described in the book.  Using a language like R is all about building on the tested work of others, so this is key. Ongoing work is described, but this will be out of  date quickly.  It may have been useful to have a place for social and formal exchanges and updates.  Think of the book as a nexus for social

Overall,  is very well done,  I expect to use several of the examples for applications. I have talked to two other people that have been reading and scanning it, and they also enjoyed its approach.

" ....  Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, guides you through every step: defining problems, identifying data, crafting and optimizing models, writing effective R code, interpreting results, and more.
 Each chapter focuses on one of today’s most important applications for predictive analytics, giving you the skills and knowledge to put models to work–and gain maximum value from them. ... " 

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