Hyper-heuristic framework for sequential semi-supervised classification based on core clustering
Existing stream data learning models with limited labeling have many limitations, most importantly, algorithms that suffer from a limited capability to adapt to the evolving nature of data, which is called concept drift. Hence, the algorithm must overcome the problem of dynamic update in the interna...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Multidisciplinary Digital Publishing Institute
2020
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| Online Access: | http://psasir.upm.edu.my/id/eprint/89236/1/HYPER.pdf http://psasir.upm.edu.my/id/eprint/89236/ https://www.mdpi.com/2073-8994/12/8/1292 |
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