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Predictive Data Mining: A Practical Guide

Predictive Data Mining: A Practical Guide

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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. 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.

Details of Book

ISBN13: 9781558604032
ISBN10: 1558604030
Language: English
Publisher: Morgan Kaufmann
Publication Year: 1997
Format: Paperback

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A note on book covers: while we do our best to ensure the accuracy of cover images, ISBNs may at times be reused for different editions of the same title which may hence appear as a different cover.

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  • One Line Summary

    Essential guide for developers on practical data mining.

  • Who is this book for?

    If you're interested in understanding the nuts and bolts of data mining, this book offers a thorough technical perspective. It walks you through developing your own applications and highlights real-world case studies to illustrate potential challenges and solutions. It's particularly good for those who want a comprehensive, practical roadmap beyond theory.

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