Rule learning for classification based on neighborhood covering reduction

@article{Du2011RuleLF,
  title={Rule learning for classification based on neighborhood covering reduction},
  author={Yong Du and Qinghua Hu and Pengfei Zhu and Peijun Ma},
  journal={Inf. Sci.},
  year={2011},
  volume={181},
  pages={5457-5467}
}
Rough set theory has been extensively discussed in the domain of machine learning and data mining. Pawlak’s rough set theory offers a formal theoretical framework for attribute reduction and rule learning from nominal data. However, this model is not applicable to numerical data, which widely exist in real-world applications. In this work, we extend this framework to numerical feature spaces by replacing partition of universe with neighborhood covering and derive a neighborhood covering… CONTINUE READING
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