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IJCAI
2007

Extracting Propositional Rules from Feed-forward Neural Networks - A New Decompositional Approach

8 years 11 months ago
Extracting Propositional Rules from Feed-forward Neural Networks - A New Decompositional Approach
In this paper, we present a new decompositional approach for the extraction of propositional rules from feed-forward neural networks of binary threshold units. After decomposing the network into single units, we show how to extract rules describing a unit’s behavior. This is done using a suitable search tree which allows the pruning of the search space. Furthermore, we present some experimental results, showing a good average runtime behavior of the approach.
Sebastian Bader, Steffen Hölldobler, Valentin
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2007
Where IJCAI
Authors Sebastian Bader, Steffen Hölldobler, Valentin Mayer-Eichberger
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