Concept Drifting Detection on Noisy Streaming Data in Random Ensemble Decision Trees
Although a vast majority of inductive learning algorithms has been developed for handling of the concept drifting data streams, especially the ones in virtue of ensemble classification models, few of them could adapt to the detection on the different types of concept drifts from noisy streaming data...
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Main Authors: | LI, Peipei, Hu, X., LIANG, Qianhui (Althea), GAO, Yunjun |
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Format: | text |
Language: | English |
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Institutional Knowledge at Singapore Management University
2009
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Online Access: | https://ink.library.smu.edu.sg/sis_research/466 http://dx.doi.org/10.1007/978-3-642-03070-3_18 |
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Institution: | Singapore Management University |
Language: | English |
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