We’ve made a new release of MOA 20.07
The new features of this release are:
- New multi-page layout
- New moa-kafka module for reading instances from a Kafka topic
- Adaptive Random Forest defaults now align with original ARF_fast publication
- Addition of the Streaming Random Patches algorithm
- Heitor Murilo Gomes, Jesse Read, and Albert Bifet. “Streaming random patches for evolving data stream classification.” In 2019 IEEE International Conference on Data Mining (ICDM), pp. 240-249. IEEE, 2019.
- Accuracy-updated ensembles can now use base learners that are not just Hoeffding Trees
- No-Change classifier now available in Lite view mode
- Addition of the ConfStream clustering algorithm
- Carnein M, Trautmann H, Bifet A and Pfahringer B (2020), “confStream: Automated Algorithm Selection and Configuration of Stream Clustering Algorithms”, To appear in 14th Learning and Intelligent Optimization Conference (LION 14)
- Carnein M, Trautmann H, Bifet A and Pfahringer B (2019), “Towards Automated Configuration of Stream Clustering Algorithms”, In Workshop on Automated Data Science at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD ’19)
- Bug fixes
You can find the download link for this release on the MOA homepage.
The MOA Team