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School of Computer Science and Statistics ECTS Module Descriptor Academic Year Module Code Module Title Pre-requisites 2011-2012 ST4003 Introduction to Data Mining ST3007 – Multivariate Analysis and Applied Forecasting ECTS Chief Examiner 10 Dr. Myra O’ Regan Teaching Staff Dr. Myra O’ Regan Delivery Aims Learning Outcomes 4 lectures and 1 lab per week over MT. The aim of the course is to introduce the students to a set of techniques including classification trees, neural networks, ensemble methods and support vector machines. Methods to evaluate models will also be discussed. To understand the theory and be able to apply the following techniques to a set of data Classification trees Neural Networks Association rules Ensemble methods Random Forests Boosting Support vector machines Evaluation of models Syllabus Introduction Overview Handling Missing data Classification Trees Association Rules Neural Nets Support vector machines Evaluating Models Ensemble methods Random Forests Boosting methods Assessment Students will be required to carry out a project employing the above techniques on a set of data using R School of Computer Science and Statistics ECTS Module Descriptor Bibliography Ayres, I. Supercrunchers, How anything can be predicted, John Murray, 2007. Berry M. J, A., & Linoff, G. Data Mining Techniques 3rd Edition , John Wiley & sons, 1997 Bishop, Christopher, Pattern Recognition and Machine Learning, Springer Science, 2006. Breiman, L., Friedman, J. H. Olshen, R. A. & Stone, C. J. Classification and regression Trees, Chapman and Hall,1984 Davenport, T.H. Harris, J.G. Competing on Analytics, The New Science of Winning, Harvard Business School Press, 2007. Hastie Trevor, Tibshirani, R., Friedman, J. The Elements of Statistical Learning, 2nd Edition, Springer Series, 2009 Ripley, B. D. Pattern recognition and Neural Networks, Cambridge University Press, 1996 Tan, Pang-Ning Steinbach, M. Kumar, V. Introduction to Data Mining, Pearson, 2006 Webb, Andrew, Statistical Pattern Recognition 2nd Edition, Wiley, 2002. Website