Rough set based approaches to feature selection for Case-Based Reasoning classifiers

@article{Salam2011RoughSB,
  title={Rough set based approaches to feature selection for Case-Based Reasoning classifiers},
  author={Maria Salam{\'o} and Maite L{\'o}pez-S{\'a}nchez},
  journal={Pattern Recognition Letters},
  year={2011},
  volume={32},
  pages={280-292}
}
This paper investigates feature selection based on rough sets for dimensionality reduction in Case-Based Reasoning classifiers. In order to be useful, Case-Based Reasoning systems should be able to manage imprecise, uncertain and redundant data to retrieve the most relevant information in a potentially overwhelming quantity of data. Rough Set Theory has been shown to be an effective tool for data mining and for uncertainty management. This paper has two central contributions: (1) it develops… CONTINUE READING
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