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...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Multidisciplinary Digital Publishing Institute
2020
|
| Online Access: | http://psasir.upm.edu.my/id/eprint/89236/1/HYPER.pdf |