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    Predictive Data Mining: A Practical Guide (The Morgan Kaufmann Series in Data Management Systems)

    By Sholom M. Weiss

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    The potential business advantages of data mining are well documented in publications for executives and managers. However, developers implementing major data-mining systems need concrete information about the underlying technical principles—and their practical manifestations—in order to either integrate commercially available tools or write data-mining programs from scratch. This book is the first technical guide to provide a complete, generalized roadmap for developing data-mining applications, together with advice on performing these large-scale, open-ended analyses for real-world data warehouses.

    Note: If you already own Predictive Data Mining: A Practical Guide, please see ISBN 1-55860-477-4 to order the accompanying software. To order the book/software package, please see ISBN 1-55860-478-2.

    + Focuses on the preparation and organization of data and the development of an overall strategy for data mining.
    + Reviews sophisticated prediction methods that search for patterns in big data.
    + Describes how to accurately estimate future performance of proposed solutions.
    + Illustrates the data-mining process and its potential pitfalls through real-life case studies.
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