What are the different types of data drift?
An example of an AI chatbot conversation about types of data drift in machine learning.
What are the different types of data drift?
Data drift refers to changes in the data distribution over time. The main types are covariate shift, prior probability shift, and concept drift.
Can you explain covariate shift in more detail?
Covariate shift occurs when the input features change, but the relationship between the input and output remains the same.
What about concept drift?
Concept drift happens when the underlying relationship between input features and the target variable changes over time.
How can I detect data drift in my model?
You can use statistical tests, monitoring model performance, or visualizations to detect data drift.
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