Alfredo Pulvirenti, University of Catania - Department of Clinical and Molecular Biomedicine, Italy

Tools and techniques for data mining
This tutorial will provide a basic introduction to data mining and statistical learning techniques. Topics include: algorithms for data mining (e.g., clustering, dimensionality reduction, recommender systems, association rule mining), basic statistical modeling (e.g., logistic and non-linear regression), supervised learning (parametric/non-parametric algorithms, support vector machines). The tutorial will also present some case studies applications together with their implementation with the R statistical programming language (www.r-project.org/).

References
Mining of Massive Datasets (http://i.stanford.edu/~ullman/mmds.html)