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2002

RIONA: A New Classification System Combining Rule Induction and Instance-Based Learning

9 years 7 months ago
RIONA: A New Classification System Combining Rule Induction and Instance-Based Learning
The article describes a method combining two widely-used empirical approaches to learning from examples: rule induction and instance-based learning. In our algorithm (RIONA) decision is predicted not on the basis of the whole support set of all rules matching a test case, but the support set restricted to a neighbourhood of a test case. The size of the optimal neighbourhood is automatically induced during the learning phase. The empirical study shows the interesting fact that it is enough to consider a small neighbourhood to achieve classification accuracy comparable to an algorithm considering the whole learning set. The combination of k-NN and a rule-based algorithm results in a significant acceleration of the algorithm using all minimal rules. Moreover, the presented classifier has high accuracy for both kinds of domains: more suitable for k-NN classifiers and more suitable for rule based classifiers.
Grzegorz Góra, Arkadiusz Wojna
Added 19 Dec 2010
Updated 19 Dec 2010
Type Journal
Year 2002
Where FUIN
Authors Grzegorz Góra, Arkadiusz Wojna
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