Hyper-heuristic framework for sequential semi-supervised classification based on core clustering

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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Bibliographic Details
Main Authors: Adnan, Ahmed, Muhammed, Abdullah, Abd Ghani, Abdul Azim, Abdullah, Azizol, Huyop @ Ayop, Fahrul Hakim
Format: Article
Language:English
Published: Multidisciplinary Digital Publishing Institute 2020
Online Access:http://psasir.upm.edu.my/id/eprint/89236/
http://psasir.upm.edu.my/id/eprint/89236/1/HYPER.pdf

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