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

Weiss, Sholom M.

Softcover

ISBN 10: 1558604030 ISBN 13: 9781558604032

Publisher: Morgan Kaufmann Publishers Inc., 1997

Synopsis

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

About this title

Review

"I enjoy reading PREDICTIVE DATA MINING. It presents an excellent perspective on the theory and practice of data mining. It can help educate statisticians to build alliances between statisticians and
data miners."
--Emanuel Parzen, Distinguished Professor of Statistics, Texas A&M University

From the Back Cover

Note: If you already own Predictive Data Mining: A Practical Guide, please click here to order the accompanying software. To order the book/software package, please click here.

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.

"I enjoy reading PREDICTIVE DATA MINING. It presents an excellent perspective on the theory and practice of data mining. It can help educate statisticians to build alliances between statisticians and data miners."
--Emanuel Parzen, Distinguished Professor of Statistics, Texas A&M University|Note: If you already own Predictive Data Mining: A Practical Guide, please click here to order the accompanying software. To order the book/software package, please click here.

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.

"I enjoy reading PREDICTIVE DATA MINING. It presents an excellent perspective on the theory and practice of data mining. It can help educate statisticians to build alliances between statisticians and data miners."
--Emanuel Parzen, Distinguished Professor of Statistics, Texas A&M University

Edition details

• Publisher: Morgan Kaufmann Publishers Inc.
• Publication date: 1997
• ISBN 10: 1558604030
• ISBN 13: 9781558604032
• Binding: Paperback
• Language: English
• Number of pages: 244