Sequential extreme learning machines for class imbalance and concept drift
Class imbalance and concept drift are two problems commonly exist in sequential learning. A weighted online sequential extreme learning machine (WOS-ELM) algorithm is proposed that has a distinctive feature of class imbalance learning (CIL) in both the chunk-by-chunk and one-by-one modes. A new samp...
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| Format: | Thesis |
| Language: | English |
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2015
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| Online Access: | https://hdl.handle.net/10356/65290 |