Data Meaning and Applications

Course Code : IA345

Time Hours : 18 hours

Time Periods : not available yet

Lecturers :

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Objective

The aim of this course is to address real problems with the various tools described in other courses and with particular attention for large and high-dimensional data sets. Several software such as R, SAS will be used. Performance and comparisons of methods commonly used in data mining will be studied.

Contents

  •  Text mining
  •  Web usage mining
  •  Bioinformatics
  •  Marketing
  •  Recommendation systems
  •  E-commerce

References

  •  The Elements of Statistical Learning : Data Mining, Inference, and Prediction. Trevor Hastie Robert Tibshirani Jerome Friedman. Springer (2009)
  •  FactoMineR : Factor Analysis and Data Mining. R, HUSSON F., JOSSE J., LE S., MAZET J., 2008, R package version 1.09.
  •  HAND D., MANNILA H., SMYTH P., Principles of Data Mining, The MIT Press, New York, 2001.