A comparative evaluation of data mining classification techniques on medical trauma data

The purpose of this research was to determine the extent to which a selection of data mining classification techniques (specifically, Discriminant Analysis, Decision Trees, and three artifical neural network models - Backpropogation, Probablilistic Neural Networks, and the Radial Basis Function) are able to correctly classify cases into the different categories of an outcome measure from a given set of input variables (i.e. estimate their classification accuracy) on a common database.

Grantor dc:publisher.institution

Department of Statistical Sciences

Year dc:date.issued

2004

Author dc:creator

• Ramaboa, Kutlwano K K M

Advisor dc:contributor.advisor

• Wegner, Trevor

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/11427/5973

OAI identifier oai:identifier

oai:open.uct.ac.za:11427/5973