C4.5: programs for machine learning
C4.5: programs for machine learning
The nature of statistical learning theory
The nature of statistical learning theory
Symbolic Representation of Neural Networks
Computer - Special issue: neural computing: companion issue to Spring 1996 IEEE Computational Science & Engineering
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Classification for accuracy and insight: a weighted sum approach
AusDM '07 Proceedings of the sixth Australasian conference on Data mining and analytics - Volume 70
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Many classifiers achieve high levels of accuracy but have limited use in real world problems because they provide little insight into data sets, are difficult to interpret and require expertise to use. In areas such as health informatics not only do analysts require accurate classifications but they also want some insight into the influences on the classification. This can then be used to direct research and formulate interventions. This research investigates the practical applications of Automated Weighted Sum, (AWSum), a classifier that gives accuracy comparable to other techniques whist providing insight into the data. AWSum achieves this by calculating a weight for each feature value that represents its influence on the class value. The merits of AWSum in classification and insight are tested on a Cystic Fibrosis dataset with positive results.