An accurate machine learning model can still cause problems if it exhibits unexpected behaviors not identified during testing.
For example, a sentiment analysis model may perform well during training, but upon deploying it, the model incorrectly labels certain positive reviews as negative when rephrasing using negative words.
Testing the behaviors of an ML model can help us identify areas for improvement. This article and video will show you how to test the behaviors of your ML model with behave.