School of Mathematics and Statistics Home | About the school | Contact | Courses | Research | Personnel list

Courses in Mathematics and Statistics Level 1 Modules Level 2 Modules Level 3 Modules Level 4 Modules Level 5 Modules Honours timetable 2011/2012 Sem. 1 2011/2012 Sem. 2 2012/2013 Sem. 1 & Sem. 2 2013/2014 Sem. 1 & Sem. 2

MT5759 KNOWLEDGE DISCOVERY AND DATAMINING This module is one of the compulsory modules for the MSc in Applied Statistics and Datamining. This module is also an option for MMath students in Statistics or Mathematics. Contemporary data collection can be automated and on a massive scale e.g. credit card transaction databases. Large databases potentially carry a wealth of important information that could inform business strategy, identify criminal activities, characterise network faults etc. These large scale problems may preclude the standard carefully constructed statistical models, necessitating highly automated approaches. Aims This module aims to give students historical, theoretical and practical coverage of the most prevalent datamining methods. By the end of the course students will: be able to match datamining problems to their suite of methods, understand the imperatives that define datamining solutions and have experience in applying their methods to real data using industry standard software packages. Syllabus This course covers many of the methods found under the banner of "Datamining", building from a theoretical perspective but ultimately teaching practical application. Topics covered include: historical/philosophical perspectives, model selection algorithms & optimality measures, tree methods, bagging and boosting, neural nets, and classification in general. Practical applications build sought-after skills in the commercial packages SAS and SPSS. Textbooks To be finalised. Assessment Two hour examination: 40% Continuous assessment: 60% Prerequisites Any of the following: MT3606, MT4607, MT5753 Availability Every year in semester 2 at 11 Lecturer Dr C R Donovan Click here to see the University Course Catalogue entry. Revised: JOC (September 2010)