What do you think?
Rate this book
Predictive Data Mining: A Practical Guide
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.
A state-of-the-art data-mining software kit accompanies the book. The software, which is delivered through a special web site, is a collection of routines for efficient mining of big data. Both classical and the more computationally expensive state-of-the-art prediction methods are included. Using a standard spreadsheet data format, this kit implements all of the data-mining tasks described in the book. The software is available for Windows 95/NT and Unix platforms (no need to specify when ordering).
* 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.
A state-of-the-art data-mining software kit accompanies the book. The software, which is delivered through a special web site, is a collection of routines for efficient mining of big data. Both classical and the more computationally expensive state-of-the-art prediction methods are included. Using a standard spreadsheet data format, this kit implements all of the data-mining tasks described in the book. The software is available for Windows 95/NT and Unix platforms (no need to specify when ordering).
* 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.
228 pages, Paperback
First published August 1, 1997
3 people want to read
Ratings & Reviews
Friends & Following
Create a free account to discover what your friends think of this book!
Community Reviews
No one has reviewed this book yet.