Data Mining and its Business Applications - MATH5836
Faculty: Faculty of Science
School: School of Mathematics and Statistics
Course Outline: http://www.maths.unsw.edu.au/
Campus: Sydney
Career: Postgraduate
Units of Credit: 6
EFTSL: 0.12500 (more info)
Indicative Contact Hours per Week: 2
CSS Contribution Charge: 2 (more info)
Tuition Fee: See Tuition Fee Schedule
Further Information: See Class Timetable
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Description
Topics include: choosing the right data mining tool for your data, linear methods (logistic regression and generalized linear models) and data mining, clustering methods, decision trees, multivariate adaptive regression splines, wavelet smoothing, hybrid models, neural networks, support vector machines, bagging and boosting methods. Case studies of industry-based data mining projects feature prominently. The most recent data mining software is used to illustrate the methods.