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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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| Publicat a: | Proc SIAM Int Conf Data Min |
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| Autors principals: | , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
2014
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| Matèries: | |
| Accés en línia: | 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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