FALL: A Modular Adaptive Learning Platform for Streaming Data
Author:
Affiliation:
1. University of Auckland,School of Computer Science,Auckland,New Zealand
2. Eindhoven University of Technology,Eindhoven,The Netherlands
3. University of Waikato and LTCI, Télécom Paris, IP-Paris
Funder
New Zealand Government
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10184508/10184509/10184752.pdf?arnumber=10184752
Reference13 articles.
1. Recurring concept memory management in data streams: exploiting data stream concept evolution to improve performance and transparency
2. A Probabilistic Framework for Adapting to Changing and Recurring Concepts in Data Streams
3. Recurring concept meta-learning for evolving data streams
4. RCD: A recurring concept drift framework
5. Deepchecks: A library for testing and validating machine learning models and data;chorev;Journal of Machine Learning Research,2022
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