Databricks Certified Machine Learning Professional — Question 80

A data scientist has developed a model to predict whether or not it will rain using the expected temperature and expected cloud coverage. However, the proportion of days where it actually rains has increased dramatically from the proportion in the data on which the model was trained.

Which type of drift is present in the above scenario?

Answer options

• A. Feature drift
• B. Label drift
• C. Prediction drift
• D. Concept drift

Correct answer: B

Explanation

The scenario indicates that the actual outcome of rain (the labels) has changed significantly from the data used for training the model, which means label drift is occurring. Feature drift would involve changes in the input features, prediction drift would relate to the output predictions changing over time, and concept drift refers to changes in the underlying relationship between features and labels, but the primary issue here is the shift in the actual labels.