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GECCO'2006: Bounding XCS’s Parameters for Unbalanced Datasets
This document discusses bounding the parameters of the XCS learning algorithm for imbalanced datasets. It outlines analyzing XCS's performance on imbalanced data, the contribution of its components, and approaches to facilitate learning minority class regions. The document will describe XCS and the domain, present experimentation, discuss how XCS handles class imbalances, provide guidelines for parameter tuning, consider online adaptation, and draw conclusions.
