STUDD: a student–teacher method for unsupervised concept drift detection

Author:

Cerqueira VitorORCID,Gomes Heitor Murilo,Bifet Albert,Torgo Luis

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Reference48 articles.

1. Baena-Garcıa, M., del Campo-Ávila, J., Fidalgo, R., Bifet, A., Gavalda, R., & Morales-Bueno, R. (2006). Early drift detection method. In Fourth international workshop on knowledge discovery from data streams (Vol. 6, pp. 77–86).

2. Benavoli, A., Corani, G., Mangili, F., Zaffalon, M., & Ruggeri, F. (2014). A Bayesian Wilcoxon signed-rank test based on the Dirichlet process. In International conference on machine learning (pp. 1026–1034). PMLR.

3. Benavoli, A., Corani, G., Demšar, J., & Zaffalon, M. (2017). Time for a change: A tutorial for comparing multiple classifiers through Bayesian analysis. The Journal of Machine Learning Research, 18(1), 2653–2688.

4. Bifet, A. (2017). Classifier concept drift detection and the illusion of progress. In International conference on artificial intelligence and soft computing (pp. 715–725). Springer.

5. Bifet, A., & Gavalda, R. (2007). Learning from time-changing data with adaptive windowing. In Proceedings of the 2007 SIAM international conference on data mining (pp. 443–448). SIAM.

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