CT-AI · Question #80
A ML engineer is trying to determine the correctness of the new open-source implementation *X", of a supervised regression algorithm implementation. R-Square is one of the functional performance…
The correct answer is C. Compare the R-Square score of the model obtained using two different implementations that. This approach directly compares the performance of two implementations of the same algorithm. If both implementations produce similar R-Square scores on the same training and testing data, it suggests that the new implementation "X" is correct.
Question
A ML engineer is trying to determine the correctness of the new open-source implementation *X", of a supervised regression algorithm implementation. R-Square is one of the functional performance metrics used to determine the quality of the model. Which ONE of the following would be an APPROPRIATE strategy to achieve this goal?
Options
- AAdd 10% of the rows randomly and create another model and compare the R-Square scores of
- BTrain various models by changing the order of input features and verify that the R-Square score
- CCompare the R-Square score of the model obtained using two different implementations that
- DDrop 10% of the rows randomly and create another model and compare the R-Square scores of
How the community answered
(31 responses)- A6% (2)
- B16% (5)
- C74% (23)
- D3% (1)
Explanation
This approach directly compares the performance of two implementations of the same algorithm. If both implementations produce similar R-Square scores on the same training and testing data, it suggests that the new implementation "X" is correct.
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