- Title
- AWSum -Combining classification with knowledge acquisition
- Creator
- Quinn, Anthony; Stranieri, Andrew; Yearwood, John; Hafen, Gaudenz; Jelinek, Herbert
- Date
- 2008
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/104023
- Identifier
- vital:11003
- Identifier
- ISSN:1673-7288
- Abstract
- Many classifiers achieve high levels of accuracy but have limited applicability in real world situations because they do not lead to a greater understanding or insight into the way features influence the classification. In areas such as health informatics a classifier that clearly identifies the influences on classification can be used to direct research and formulate interventions. This research investigates the practical aplications of Automated Weighted Sum, (AWSum), a classifier that provides accuracy comparable to other techniques whist providing insight into the data. This is achieved by calculating a weight for each feature value that represents its influence on the class value. The merits of this approach in classification and insight are evaluated on a Cystic Fibrosis and diabetes datasets with positive results.
- Relation
- International Journal of Software and Informatics Vol. 2, no. 2 (2008), p. 199-214
- Rights
- © Copyright by Institute of Software, the Chinese Academy of Sciences
- Rights
- This metadata is freely available under a CCO license
- Subject
- Data mining; Classification; Knowledge acquisition; Weighted sum
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