Identifying and repairing model drift Performance loss in AI models comes in three flavors. Concept drift entails changes in the characteristics of the dependent variable.

The ensemble learning model can effectively detect drift and utilize diversity to improve the performance of adapting to drift. However, local concept drift can occur in different types at different ...

To address this issue, a semi-supervised active learning neural network for data streams with concept drift is proposed to build an accurate classification model from incompletely labeled data. First, ...

Further, emerging strategies employing fuzzy formal concept analysis have enabled more nuanced drift detection, particularly in complex scenarios such as fake news identification [3].