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A Neighborhood Rough Sets-Based Attribute Reduction Method Using Lebesgue and Entropy Measures
For continuous numerical data sets, neighborhood rough sets-based attribute reduction is an important step for improving classification performance. However, most of the traditional reduction algorithms can only handle finite sets, and yield low accuracy and high cardinality. In this paper, a novel...
Kaydedildi:
| Yayımlandı: | Entropy (Basel) |
|---|---|
| Asıl Yazarlar: | , , , |
| Materyal Türü: | Artigo |
| Dil: | Inglês |
| Baskı/Yayın Bilgisi: |
MDPI
2019
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| Konular: | |
| Online Erişim: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7514624/ https://ncbi.nlm.nih.gov/pubmed/33266854 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/e21020138 |
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