songqiaohu/THU-Concept-Drift-Datasets-v1.0
📖These are the concept drift datasets we made, and we open-source the data and corresponding interfaces. Welcome to use them for free if there is a need.
This project provides datasets for evaluating how well machine learning models adapt to changing data patterns over time. You input data streams that simulate real-world changes, and the datasets output labeled examples with various 'drift' types—like abrupt or gradual shifts in data distribution. This is intended for data scientists, machine learning engineers, and researchers who build and test predictive models that operate on continuously updating information.
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Use this if you need to rigorously test the resilience and adaptability of your online machine learning models to different types of concept drift.
Not ideal if you are looking for ready-to-use, real-world labeled datasets without any simulated concept drift, or if you need a solution for detecting drift rather than just evaluating against it.
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Apr 16, 2024
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