A comparative evaluation of data mining classification techniques on medical trauma data
Includes bibliographical references (leaves 109-113). === 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, Probabli...
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| Format: | Dissertation |
| Language: | English |
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University of Cape Town
2014
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| Online Access: | http://hdl.handle.net/11427/5973 |
| Summary: | Includes bibliographical references (leaves 109-113). === 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. |
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