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Session:

Workshop - IWLCS

Title:

Post-Processing Clustering to Reduce XCS Variability

   

Authors:

Flavio Baronti
Alessandro Passaro
Antonina Starita

   

Abstract:

XCS is a stochastic algorithm, so it does not guarantee to produce the same results when run with the same input. When interpretability matters, obtaining a single, stable result is important. We propose an algorithm to join the rules produced from many XCS runs, based on a measure of distance between rules. We also suggest a general definition for such a measure, and show the results obtained on a complex data set.

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