Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Data Mining: Practical Machine Learning 0120884070

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

ISBN:
0120884070

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Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems) Specs:
Product NameData Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
ManufacturerMorgan Kaufmann
Retail Price $65.95
EAN-139780120884070
Specifications 
TitleData Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
ISBN0120884070
Author(s)Ian H. Witten, Eibe Frank
Release Date2005-06-08, 2005-06-22
FormatPaperback
Num of Pages560
Num. of Items1
EAN9780120884070
Edition2
Dimensions9.13 x 7.48 x 1.18 in.
Weight3 lbs.
Deal first added on:28-August-2008
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Latest 6 Reviews
Here is what people are saying about the Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
4 Star Rating  "A data mining Book for Open source tools"2009-05-08
- Reviewed By User: A2CK13I9Q01D43
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
 
5 Star Rating  "Useful addition to your shelf"2009-01-14
- Reviewed By User: A1HGDG0FN1BEIV
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.
 
5 Star Rating  "A book to understand the subject"2009-01-13
- Reviewed By User: ACE5Q745W674Q
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.
 
3 Star Rating  "Not very user-friendly, too much emphasis on Weka language"2009-01-07
- Reviewed By User: A3NQT8W16EYY6D
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.
 
3 Star Rating  "very useful academically, but not industry focused"2008-10-30
- Reviewed By User: A3VVOR5NTDKEF
It is a very clear and easy reading 'machine learning' book to read, but its not a 'data mining' book. Everyone in the industry agrees that over 80% of your time and effort is in the data preparation, yet this book has virtually no mention of data transformations or data preparation.

It is a good book that describes how algorithsm works, their pros and cons. Very useful for new starters and academics. It won't help a industry practitioner though.

Page 360 onwards to 500 are dedicated to using a freeware data mining tool named Weka.

The book was worth the buy, but I had hoped for more.

- Tim
 
2 Star Rating  "Not particularly useful"2008-07-11
- Reviewed By dboca
The material is very superficially laid out and for a book with the word "Practical" in the sub-title it contains almost no practical examples of data mining.
 
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