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The Discovery and Use of Ordinal Information on Attribute Values in Classifier Learning
conference contribution
posted on 2023-05-23, 05:40 authored by Berry, A, Cameron-Jones, RRule and tree based classifier learning systems can employ the idea of order on discrete attribute and class values to aid in classifi- cation. Much work has been done on using both orders on class values and monotonic relationships between class and attribute orders. In con- trast to this, we examine the usefulness of order specifically on attribute values, and present and evaluate three new methods for recovering or discovering such orders, showing that under some circumstances they can significantly improve accuracy. In addition we introduce the use of classifier ensembles that use random value orders as a source of variation, and show that this can also lead to significant accuracy gains.
History
Publication title
Proceedings of AI2011: Advances in Artificial Intelligence, the 24th Australasian Joint ConferenceEditors
D Wang & M ReynoldsPagination
31-40ISBN
978-3-642-25831-2Department/School
School of Information and Communication TechnologyPublisher
Springer- VerlagPlace of publication
Berlin HeidelbergEvent title
AI2011: Advances in Artificial Intelligence, the 24th Australasian Joint ConferenceEvent Venue
Perth, AustraliaDate of Event (Start Date)
2011-12-05Date of Event (End Date)
2011-12-08Rights statement
Copyright 2011 Springer-VerlagRepository Status
- Restricted