CSE3212

Data Mining

(IT)

Robert Redpath

6 points + Caulfield + One 2-hour lecture and one 2-hour tutorial per week. Second semester. Prerequisites: COT2132 or CSE2132 or equivalent.

Synopsis: This subject provides an overview of the techniques used to search for knowledge within a data set using both supervised and unsupervised learning. The techniques include Classification, Prediction, Clustering, Association discovery, Time sequence discovery, Sequential pattern discovery, Visualization, Statistical Methods, Decision Trees, Rule based methods, Neural networks, Machine learning, Genetic Algorithms and Fuzzy Systems. Students will be able to choose an appropriate technique to suit a particular situation.

Assessment: Practical Assignments 40%, Examination (2 hours)