Classiffcation for accuracy and insight: a weighted sum approach

Quinn, Anthony, Stranieri, Andrew and Yearwood, John Leighton 2007, Classiffcation for accuracy and insight: a weighted sum approach, in AusDM 2007 : Proceedings of the 6th Australasian Data Mining Conference 2007, Australian Computer Society,, pp. 203-208.

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Title Classiffcation for accuracy and insight: a weighted sum approach
Author(s) Quinn, Anthony
Stranieri, Andrew
Yearwood, John LeightonORCID iD for Yearwood, John Leighton orcid.org/0000-0002-7562-6767
Conference name Australasian Data Mining. Conference (6th : 2007 : Gold Coast, Queensland)
Conference location Gold Coast, Queensland
Conference dates 2007/12/03 - 2007/12/04
Title of proceedings AusDM 2007 : Proceedings of the 6th Australasian Data Mining Conference 2007
Publication date 2007
Series Conferences in Research and Practice in Information Technology Series
Conference series Australasian Data Mining Conference
Start page 203
End page 208
Total pages 6
Publisher Australian Computer Society
Summary This research presents a classiffer that aims to pro-vide insight into a dataset in addition to achieving classiffcation accuracies comparable to other algo-rithms. The classiffer called, Automated Weighted Sum (AWSum) uses a weighted sum approach where feature values are assigned weights that are summed and compared to a threshold in order to classify an example. Though naive, this approach is scalable, achieves accurate classiffcations on standard datasets and also provides a degree of insight. By insight we mean that the technique provides an appreciation of the in o uence a feature value has on class values, rel-ative to each other. AWSum provides a focus on the feature value space that allows the technique to iden-tify feature values and combinations of feature values that are sensitive and important for a classiffcation. This is particularly useful in ffelds such as medicine where this sort of micro-focus and understanding is critical in classiffcation.
ISBN 9781920682514
ISSN 1445-1336
Language eng
HERDC Research category EN.1 Other conference paper
Copyright notice ©2007, Australian Computer Society
Persistent URL http://hdl.handle.net/10536/DRO/DU:30101499

Document type: Conference Paper
Collection: School of Information Technology
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