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CORR
2011
Springer

A Generalized Method for Integrating Rule-based Knowledge into Inductive Methods Through Virtual Sample Creation

8 years 13 days ago
A Generalized Method for Integrating Rule-based Knowledge into Inductive Methods Through Virtual Sample Creation
Hybrid learning methods use theoretical knowledge of a domain and a set of classified examples to develop a method for classification. Methods that use domain knowledge have been shown to perform better than inductive learners. However, there is no general method to include domain knowledge into all inductive learning algorithms as all hybrid methods are highly specialized for a particular algorithm. We present an algorithm that will take domain knowledge in the form of propositional rules, generate artificial examples from the rules and also remove instances likely to be flawed. This enriched dataset then can be used by any learning algorithm. Experimental results of different scenarios are shown that demonstrate this method to be more effective than simple inductive learning.
Ridwan Al Iqbal
Added 13 May 2011
Updated 13 May 2011
Type Journal
Year 2011
Where CORR
Authors Ridwan Al Iqbal
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