Description
In order to know about the performance of a drift detector by measuring the different detection metrics, we need to know beforehand where a real drift occurs. This is only possible with synthetic datasets. The scikit-multiflow framework allows generating several kinds of synthetic data to simulate the occurrence of drifts.
| Date made available | 17 Sept 2020 |
|---|---|
| Publisher | Harvard Dataverse |
| Date of data production | 2020 - |
Research output
- 1 Article
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CURIE: a cellular automaton for concept drift detection: a cellular automaton for concept drift detection
Lobo, J. L., Del Ser, J., Osaba, E., Bifet, A. & Herrera, F., Nov 2021, In: Data Mining and Knowledge Discovery. 35, 6, p. 2655-2678 24 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile5 Citations (Scopus)4 Downloads (Pure)
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