Those studying the progress of data mining will quickly realise that the scientifically and academically charged subject has evolved rather slowly in the commercial world. This book, for when it was first written, did an excellent job of presenting the key concepts and working through them in an effective way.
Particularly attractive to those with an application development interest. The introduction to the WEKA environment offers a great set of resources difficult to ignore. Highly recommended for practitioners.
Cleary, data mining is still developing. With certain applications, the algorithms and parameters are being pushed continually further away from end-users and hidden with varying levels of automation. For others, perhaps more recent techniques, less is known and therefore a greater level of control is required to allow for adequate experimentation.
In any case, this book should well worth digesting, although it has been superceded by the second edition, Data Mining, Practical Machine Learning Tools & Techniques, 2005, which, on the whole, does the job even better - so I'd go for that unless the first edition is heavily discounted.
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