I want to develop a framework(for QA testing purpose) that validates a machine learning model. I had a lot of discussions with my peers and read articles from the google.
Most of the discussions or articles are telling machine learning model will evolve with the test data that we provide. correct me if I'm wrong.
What is the possibility of developing a framework that validates the machine learning model will give accurate results?
Few ways to test the model from the articles I read: Split and Multi-split technique, Metamorphic testing
Please also suggest any other approaches
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