Which of the following is a probable response to identifying drift in a machine learning application?
Which of the following is a probable response to identifying drift in a machine learning application?
A probable response to identifying drift in a machine learning application is retraining and deploying a model on more recent data. This allows the model to adapt to changes in the underlying data distribution and helps in maintaining its performance and accuracy.
This response involves updating the model by retraining it on more recent data to adapt to changes in the underlying data distribution and maintain its performance.
"... it can trigger a notification or an action to recreate a new model using newer data." https://www.databricks.com/blog/2019/09/18/productionizing-machine-learning-from-deployment-to-drift-detection.html
The correct answer is B. Retraining and deploying a model on more recent data12. When drift is identified in a machine learning application, one common response is to retrain the model on more recent data to account for the changes12. This can help to maintain the performance and accuracy of the model