Books
by
Kuiyu Chang
—
last modified
Aug 25, 2008 03:23 PM
You should consider getting at least the text. The references are listed in ascending order of difficulty/levels, i.e. first book is introductory, last book is the hardest.
Main Text
- Tan, Steinbach, Kumar, Introduction to Data Mining, Pearson Addision Wesley, 2005
- Presented from a Machine Learning perspective
References
- Jiawei Han & Micheline Kamber, Data Mining: Concepts and techniques, 2nd ed, Morgan Kaufmann, 2006
- Presented from a Database/Datawarehousing point of view
- Hand, Mannila, Smyth, "Principles of Data Mining", MIT Press, 2001
- Mitchell, "Machine Learning", McGraw Hill, 1997
- Duda, Hart, Stork, "Pattern Classification", 2nd ed, 2001
- Christopher Bishop, Neural Networks for Pattern Recognition, Oxford University Press, 12th reprint, 1995
- Hastie, Tibshirani, Friedman, "The Elements of Statistical Learning: Data Mining, Inference, and Prediction", Springer Verlag, 2001
- Soumen Chakrabarti, "Mining the web", Morgan Kaufmann Publishers, 2003
Practical Guides
- Elizabeth Vitt, Michael Luckervic, Stacia Misner, "Making Better Business Intelligence Decisions Faster", Microsoft Press, 2002
- Claude Seidman, "Data Mining with Microsoft SQL Server 2000", Microsoft Press, 2001
