[Solved] You have a data science model that outputs predictions as a list.... Which approach below best applies regression testing? | Testing Fundamentals

Testing Fundamentals - Testing Types and Levels

You have a data science model that outputs predictions as a list. You want to automate regression testing to check if new code changes break the model's output. Which approach below best applies regression testing?

ADelete old predictions and start fresh after every change

BTrain a new model with updated data and ignore old predictions

CVisualize new predictions only to check for differences

DSave previous predictions and compare them with new predictions after changes

Step-by-Step Solution

Solution:

Step 1: Understand regression testing in model outputs
Regression testing means re-running tests and comparing new outputs to old outputs to detect unintended changes.
Step 2: Evaluate options for best fit
Save previous predictions and compare them with new predictions after changes saves old predictions and compares them to new ones, matching regression testing. Others ignore old outputs or delete them, which is not regression testing.
Final Answer:
Save previous predictions and compare them with new predictions after changes -> Option D
Quick Check:
Regression testing = compare old and new outputs [OK]

Quick Trick: Keep old outputs to compare with new after changes [OK]

Common Mistakes:

MISTAKES

Ignoring old outputs in testing
Assuming visualization replaces regression tests
Deleting old results before testing

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Which approach below best applies regression testing?

Step 1: Understand regression testing in model outputs

Step 2: Evaluate options for best fit

Final Answer:

Quick Check:

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