ISA-IAPS: Introduction to statistic learning



"Classic statistics are based on the study of a limited number of measured characteristics from a small number og individuals.It developed notions of estimation and tests founded on very restrictive hypotheses of probability.
However in practice the individuals observed are frequently described by a huge number of characteristics. The methods of data analysis allow a global study of individuals and variables generally using suggestive graphic representations".
(Jean-Marie Bouroche and Gilbert Saporta, "L'analyse des données")

Duration: 21h



Recommended reading

C. Bishop, Pattern Recognition and Machine Learning. Springer, 2006.

P. Besse, Data Mining 2: Modélisation statistique et apprentissage. Polycopié Université Paul Sabatier de Toulouse (, 2003.

R. Duda, P. Hart, and D. Stork, Pattern Classification, John Wiley & Sons, 2001.

T. Hastie, R. Tibshirani, and J. Fridman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Springer-Verlag, 2001.

  Year 2006/2007
Last update: 05-DEC-06
Last validation:

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