4.0 von 5 Sternen
A book from practitioners, 30. März 2000
Many books have been written on the algorithms used for data mining (e.g., machine learning, statistics). This is not yet another one.
This book is geared at people who want to derive insight and take action in a business setting. It is now well known that the algorithmic step is only a small part of the iterative knowledge discovery process, yet few books enlighten the users with the issues involved.
This book has a small section on the algorithms, but concentrates on the often-overlooked PROCESS of data mining (sometimes called knowledge discovery) and the problems associated with this process in practice.
Michael and Gordon are practitioners who have used multiple data mining tools and techniques. They know the problems and describe them well, sharing their real-life experiences through actual case studies. For example, people rarely appreciate the main problem with association algorithms: the number of uninteresting rules they generate. Now I can show them pages 426-428.
The few things that I didn't like were the use of non-standard terminology in a few cases. For example, directed instead of supervised; prediction instead of regression. While the common terms aren't great, they're standard now. The book also has few references. Someone readers will want to read more details about specific areas and will not find needed references.
Overall, it's a well written book, easy to read, with nice analogies to the world of photography.