Abstract
scikit-multiflow is a framework for learning from data streams and multi-output learning in Python. Conceived to serve as a platform to encourage the democratization of stream learning research, it provides multiple state-of-the-art learning methods, data generators and evaluators for different stream learning problems, including single-output, multi-output and multi-label. scikit-multiflow builds upon popular open source frameworks including scikit-learn, MOA and MEKA. Development follows the FOSS principles. Quality is enforced by complying with PEP8 guidelines, using continuous integration and functional testing. The source code is available at https://github.com/scikit-multiflow/scikit-multiflow.
| Original language | English |
|---|---|
| Journal | Journal of Machine Learning Research |
| Volume | 19 |
| Publication status | Published - 1 Oct 2018 |
| Externally published | Yes |
Keywords
- Drift Detection
- Machine Learning
- Multi-output
- Python
- Stream Data