Synopsis
Deals with discovering hidden data and unexpected patterns and rules in large databases. Offers a comprehensive introduction to data mining. Paper.
"synopsis" may belong to another edition of this title.
About the Author
Peter Adriaans is a director of Syllogic, where he is responsible for the development of tools for the management of client/server systems and databases. The basis for Syllogic's activities is the intergration of artificial intelligence techniques, machine learning, object orientation and database management systems.
Dolf Zantinge has broad experience setting up large client/server projects. He is a director of Syllogic. The basis for Syllogic's activities is the intergration of artificial intelligence techniques, machine learning, object orientation and database management systems.
0201403803AB04062001
From the Back Cover
Data Mining deals with discovering hidden knowlege, unexpected patterns and rules in large databases. It can bring significant gains to organizations, for example, through better targeted marketing and enhanced internal performance. If you have large data sets (for example, large quantities of financial data, extensive customer databases or sales records) you can benefit from this newly emerging field. But setting up a data mining environment is not a trivial task. The long-term goal must be to create a self-learning organization that makes optimal use of the information it generates.
This is the first book to offer a comprehensive introduction to data mining. Its aim is to provide essential insights and guidelines to help you make the right decisions when setting up a data mining environment.
It offers answers to questions such as:
- What is Data Mining?
- Which techniques are suitable for my data?
- How do I set up a data mining environment?
- How do I justify the costs?
The whole data mining process, including data selection, cleaning, coding, different pattern recognition techniques and reporting, is illustrated by means of an extensive case study and numerous answers.
Audience- General management and IT managers
0201403803B04062001
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Data Mining
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Data Mining
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ISBN 10: 0201403803
ISBN 13: 9780201403800
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ISBN 10: 0201403803
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Data Mining
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ISBN 13: 9780201403800
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