Statistical methods for data mining

Course Description

Statistical methods applied on solving prediction, classification and clustering problems in mining high dimensional data. Foundation of of statistical analysis. Selection of some linear and nonlinear models. Selection of multivariate exploratory techniques. Supervised and unsupervised methods. Data mining case studies in bioinformatics, finance, text classification and in web information retrieval.

Study Programmes

Postgraduate doctoral study programme


Trevor Hastie, Robert Tibshirani, Jerome Friedman (2013.), The Elements of Statistical Learning: Data Mining, Inference and Prediction, Springer Science & Business Media
Michael W. Berry (2013.), Survey of Text Mining: Clustering, Classification, and Retrieval, Springer Science & Business Media
Barbara G. Tabachnick, Linda S. Fidell (2001.), Using Multivariate Statistics, 4th Ed., Allyn & Bacon

For students


ID 154765
  Summer semester
L0 English Level