AWSum-Combining Classi cation with Knowledge Aquisition
Received:October 15, 2008  Revised:December 19, 2008  Download PDF
Anthony Quinn,Andrew Stranieri,John Yearwood,Gaudenz Hafen,Herbert Jelinek. AWSum-Combining Classi cation with Knowledge Aquisition. International Journal of Software and Informatics, 2008,2(2):199~214
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Anthony Quinn  Andrew Stranieri  John Yearwood  Gaudenz Hafen  Herbert Jelinek
Abstract:Many classi ers 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 in uence the classi cation. In areas such as health informatics a classi er that clearly identi es the in uences on classi cation can be used to direct research and formulate interventions. This research investigates the practical applications of Automated Weighted Sum, (AWSum), a classi er 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 in uence on the class value. The merits of this approach in classi cation and insight are evaluated on a Cystic Fibrosis and Diabetes datasets with positive results.
keywords:data mining  classification  knowledge acquisition  weighted sum
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