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A quick tutorial for those who have downloaded and installed the trial version of Chameleon Statistics is available here.

Users of Chameleon Statistics may find the following books of interest:

A. Agresti, Categorical Data Analysis, 2nd edn (Wiley, 2002)
E. Alpaydin, Introduction to Machine Learning (MIT Press, 2004)
C. M. Bishop, Pattern Recognition and Machine Learning (Springer, 2007)
V. Cherkassky & F. M. Mulier, Learning from Data (Wiley, 2007)
R. O. Duda, P. E. Hart & D. G. Stork, Pattern Classification, 2nd edn (Wiley, 2000)
G. Gan, C. Ma, J. Wu, Data Clustering (SIAM, 2007)
T. Hastie, R. Tibshirani & J. H. Friedman, The Elements of Statistical Learning (Springer, 2003)
J. Kogan, Introduction to Clustering Large and High-Dimensional Data (CUP, 2006)
D. J. C. Mackay, Information Theory, Inference & Learning Algorithms (CUP, 2000)
B. D. Ripley, Pattern Recognition and Neural Networks (CUP, 2008)
S. Russell & P. Norvig, Artificial Intelligence, 2nd edn (Prentice Hall, 2002)
B. Scholkopf & A. J. Smola, Learning with Kernels (MIT Press, 2001)
*Theodoridas & Koutroumbas, Pattern Recognition, 3rd edn (Academic Press, 2006)
A. R. Webb, Statistical Pattern Recognition, 2nd edn (Wiley, 2002)
I. H. Witten & E. Frank, Data Mining, 2nd edn (Morgan Kauffman, 2005)

If you would like to suggest additional references to add to this list, then please send an email to

*Recommended text.