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Statistical Modeling and Analysis for Database Marketing: Effective Techniques for Mining Big Data

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Title: Statistical Modeling and Analysis for Database Marketing: Effective Techniques for Mining Big Data
by Bruce Ratner
ISBN: 1-57444-344-5
Publisher: Chapman & Hall/CRC
Pub. Date: 28 May, 2003
Format: Hardcover
Volumes: 1
List Price(USD): $59.95
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Average Customer Rating: 5 (2 reviews)

Customer Reviews

Rating: 5
Summary: Data Mining for Database marketing
Comment: I predict that Dr. Ratner's Statistical Modeling and Analysis for Database Marketers: Effective Techniques for Mining Big Data will be on every database marketer's bookshelf. Dr Ratner has put together an assembly of chapters that provide an indispensable resource for the daily problems facing data analysts and model builders in the database/direct marketing community. In each of the seveenteen chatpers Dr. Ratner addresses a typical problem and discusses the common solution. He points out unknown working assumptions or weaknesses of the latter, and then offers better solutions, which require basic knowledge of EDA/data mining. Dr. Ratner's writing style is unique as he makes familar concepts new, and new concepts familar. Thus, the book is easy and enjoyable reading. I specially like chapter that blends statistics with the machine learning, such as the introduction of the GenIQ Model.

Rating: 5
Summary: "EDA III" for Database Marketing
Comment: I consider myself fortunate to be the first to review this book. The title aptly indicates what the book is about: Statistical Modeling and Analysis for Database Marketers: Effective Techniques for Mining Big Data. The author provides in a Tukey-esque manner a collection of solutions to common problems facing database analysts, model builders, and marketers. The book can uniquely serve as a textbook, a how-to guide, and a reference source depending on the reader's statistical training and database marketing experience. Moreover, the author actually goes where other authors provide lip service: he creates the marriage of the "old" statistical methodologies with the new machine learning influence by introducing machine learning methods specifically tailored to database assessment of optimal model performance. The book's illustrations involve real problems, real data, and better solutions. This book is a keeper!

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