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Tuesday, January 24, 2012

Data Mining Cookbook - Modeling Data for Marketing, Risk, and Customer Relationship Management (OCR) - 2001






by Olivia C. Rud , O. C. Rud , Olivia Parr Rud

About the Book

Increase profits and reduce costs by utilizing this collection of models of the most commonly asked data mining questions
In order to find new ways to improve customer sales and support, and as well as manage risk, business managers must be able to mine company databases. This book provides a step-by-step guide to creating and implementing models of the most commonly asked data mining questions. Readers will learn how to prepare data to mine, and develop accurate data mining questions. The author, who has over ten years of data mining experience, also provides actual tested models of specific data mining questions for marketing, sales, customer service and retention, and risk management. A CD-ROM, sold separately, provides these models for reader use.




Get a data mining recipe for success to increase profits and reduce costs in today's business world with-This CD-ROM provides actual, tested models of the most commonly asked data mining questions for marketing, sales, risk analysis, customer retention and support, and other key business applications. Complete, working code written in SAS will help you directly implement models, with or without an automated mining tool. With this invaluable resource, you'll be able to target the best customers, improve sales and services, and increase overall profitability for your company. Step-by-step guidance on how to create, evaluate, validate, and implement models, plus a review of the basics, are available through the companion book, Data Mining Cookbook (sold separately from Wiley). Minimum System Requirements:Windows


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2 comments:

  1. Hi chenroger,

    did you manage to find out, from where to download.
    IF you need the book,i have i can send it over to you.
    i am also looking forward to the CD, but unable to find it anywhere.
    mithun.nyal@gmail.com

    ReplyDelete

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