The subject provides students with in-depth study of data and knowledge engineering and their use in real life business. It looks into interpreting data through advanced approaches such as an ensemble of trees and clustering. Given the importance of clean and useful data for knowledge discovery, it offers thorough discussion on data pre-processing tasks including missing value imputation, corrupt data detection, discretization, and feature selection. The subject offers a study of the preservation of privacy when data mining, publishing and sharing among business organisations. It uses the current tools for knowledge discovery and future prediction.
HD/FL
One session
School of Computing and Mathematics
Only available to postgraduate students.
ITC516 Data Mining and Visualisation or equivalent.
For further information about courses and subjects outlined in the CSU handbook please contact:
The information contained in the CSU Handbook was accurate at the date of publication: May 2019. The University reserves the right to vary the information at any time without notice.