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Microsoft Exam AI-900 Topic 1 Question 21 Discussion
Actual exam question for
Microsoft's
AI-900 exam
Question #: 21
Topic #: 1
[All AI-900 Questions]
Topic #: 1
What are two metrics that you can use to evaluate a regression model? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
Suggested Answer:
A, C
A: R-squared (R2), or Coefficient of determination represents the predictive power of the model as a value between -inf and 1.00. 1.00 means there is a perfect fit, and the fit can be arbitrarily poor so the scores can be negative.
C: RMS-loss or Root Mean Squared Error (RMSE) (also called Root Mean Square Deviation, RMSD), measures the difference between values predicted by a model and the values observed from the environment that is being modeled.
https://docs.microsoft.com/en-us/dotnet/machine-learning/resources/metrics
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