What are some examples of data drift in machine learning?

What are some examples of data drift in machine learning?

Data drift occurs when the statistical properties of the target variable change over time. Examples include changes in user behavior, seasonality effects, or shifts in data collection methods.

Can you give me a specific example of data drift?

Sure! For instance, if a model predicting customer purchases was trained on data from a holiday season, it might not perform well during non-holiday periods due to different buying patterns.

How can I detect data drift in my models?

You can detect data drift using statistical tests like the Kolmogorov-Smirnov test or monitoring model performance metrics over time.

What steps can I take to mitigate data drift?

To mitigate data drift, you can retrain your models regularly, use adaptive learning techniques, or implement continuous monitoring systems.