What are the signs of data drift in machine learning models?

What are the signs of data drift in machine learning models?

Data drift occurs when the statistical properties of the target variable change over time. Signs include decreased model accuracy, unexpected predictions, and changes in feature distributions.

How can I detect data drift in my model?

You can use techniques like monitoring model performance metrics, visualizing feature distributions, and employing statistical tests to detect data drift.

What should I do if I detect data drift?

If you detect data drift, consider retraining your model with new data, adjusting your features, or implementing a more robust monitoring system.

Can data drift affect all types of models?

Yes, data drift can affect any machine learning model, regardless of its type, as it relies on the underlying data distribution.

Are there tools available to help with data drift detection?

Yes, there are several tools like Alibi Detect, NannyML, and Evidently AI that can help monitor and detect data drift.