Data Mining: Practical Machine Learning Tools and Techniques, Third Edition (The Morgan... at Dominant Systems Book Store

"The authors provide enough theory to enable practical application, and it is this practical focus that separates this book from most, if not all, other books on this subject."- Dorian Pyle, Director of Modeling at Numetrics and an internationally known author of Data Preparation for Data Mining (Morgan Kaufmann, 1999) and Business Modeling for Data Mining (Morgan Kaufmann, 2003)

"This book would be a strong contender for a technical data mining course. It is one of the best of its kind."- Herb Edelstein, Principal, Data Mining Consultant, Two Crows Consulting.

"It is certainly one of my favorite data mining books in my library"- Tom Breur, Principal, XLNT Consulting, Tilburg, The Netherlands

Customer Reviews & Comments
Customer review from the Amazon Vine™ Program (What's this?) Context for this review: I am a data miner with 20 years experience, and own the first edition of this book. Good: - Accessible writing style - Broad coverage of algorithms and data mining issues, with an eye toward practical issues - Needless technical trivia (derivations and the like) are avoided - Algorithms are completely spelled out: A competent programmer should be able to turn these descriptions into functioning code. - Third edition makes meaningful improvements on previous editions Bad(ish): - Approximately one-third of this book is now devoted to the WEKA data mining software. I have nothing against WEKA, and it is a good choice for a text such as this, since WEKA is free. In my opinion, though, this coverage consumes too many pages of this book. - Data mining draws from a number of fields with separate roots (statistics, machine learning, pattern recognition, engineering, etc.), and many techniques go by multiple names. As with many other data mining books, this one does not always point out the aliases by which data mining methods are known. The bottom line: This is still the best data mining text on the market.

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