Practice and theory of data mining

I am engaged in my first major data mining project, and as I read Witten's & Frank's book, page after page of experience answer the questions that I had been asking myself, then giving more. The book has given me the confidence to grow my abilities. Both Ian Witten and Eibe Frank have been drivers in developing the interface and collection of data mining tools called Weka developed at the University of Waikato, New Zealand.Their depth of experience shine in the book. The book has two parts. Part 1, Machine learning tools and techniques, guides the reader through the SEMMA data mining methodology (not specifically stated). Part 2, the WEKA machine learning workbench, is a guide into Weka, with detailed commentary to the underlying data mining method and theory. The contents is comprehensive, giving a detailed outline of the story line, thus giving the reader the overview and context needed to find sections of intererst rapidly. I have used other data mining texts, however the solid practical advice offered in this book sets it apart. I wish I had picked this book up twelve months ago.

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