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Classifying Imbalanced Data Streams via Dynamic Feature Group Weighting with Importance Sampling
Data stream classification and imbalanced data learning are two important areas of data mining research. Each has been well studied to date with many interesting algorithms developed. However, only a few approaches reported in literature address the intersection of these two fields due to their comp...
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| Yayımlandı: | Proc SIAM Int Conf Data Min |
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| Asıl Yazarlar: | , , , , |
| Materyal Türü: | Artigo |
| Dil: | Inglês |
| Baskı/Yayın Bilgisi: |
2014
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| Konular: | |
| Online Erişim: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4283472/ https://ncbi.nlm.nih.gov/pubmed/25568835 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1137/1.9781611973440.83 |
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