Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems),   ISBN:9780120884070

Customer Rating: 

This book provides a good overview of the uses and techniques of data mining, then drills steadily into more detail, allow the reader to determine what level of detail he is interested in learning. Practical application of the techniques via WEKA re-enforce the learning possible through the use of this book.

I am still looking for an equivalent approach for text mining, which this book addresses at a high level.

Customer Rating: 

Data Mining Sec Edition is a good book with a good support for related open source Weka system. You can test and exercize with no cost with data mining tecnique.
Good work

Customer Rating: 

This title is a most useful addition to your data mining collection, especially if you plan to do some practical experimentation with the Open Source WEKA software it describes. You do not need a degree in maths or statistics to work with this text, conversely don't expect detailed line-by-line explanations of each algorithm either. If you want that open up the Java code in the WEKA software. I note in the other reviews comments about the practical nature of the book: the authors are at Waikato University in the heart of New Zealand's dairy country, and it is this practical agricultural application that has driven the research behind the text and the software, as opposed to books written by authors working in the cloistered mathematics departments of the major universities. Recommended for serious students new or not new to the subject.

Customer Rating: 

It's the best book I know because it explains the topics in a very didactic fashion and the book refers to a computer program easily available (Weka, from the University of Waikato of New Zealand)because is Open Source.

Customer Rating: 

This book was used as one of the two textbooks in a graduate school database course. It is hard to follow and places too much emphasis on the Weka data mining language (the authors developed Weka). As a data mining beginner, I had to consult several other data mining references in addition to this book.