AWSum: Combining classification with knowledge aquisition

A. Quinn, A. Stranieri, J. Yearwood, G. Hafen, Herbert Jelinek

Research output: Contribution to journalArticle

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 identifes the influences on classifcation can be used to direct research and formulate interventions. This research investigates the practical applications of Automated Weighted Sum, (AWSum), a classifer 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 classifcation and insight are evaluated on a Cystic Fibrosis and Diabetes datasets with positive results.
Original languageEnglish
Pages (from-to)199-214
Number of pages16
JournalInternational Journal of Software Informatics
Volume2
Issue number2
Publication statusPublished - Dec 2008

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