DY0-001 · Question #75
A data scientist uses a large data set to build multiple linear regression models to predict the likely market value of a real estate property. The selected new model has an RMSE of 995 on the…
The correct answer is C. The model fails to improve meaningfully on the benchmark model. Although the new model's RMSE is technically lower (995 vs. 1,000), the five-point improvement on holdout data is negligible in most real-estate contexts and unlikely to produce meaningful business value over the existing benchmark.
Question
A data scientist uses a large data set to build multiple linear regression models to predict the likely market value of a real estate property. The selected new model has an RMSE of 995 on the holdout set and an adjusted R2 of .75. The benchmark model has an RMSE of 1,000 on the holdout set. Which of the following is the best business statement regarding the new model?
Options
- AThe model should be deployed because it has a lower RMSE.
- BThe model's adjusted R2 is exceptionally strong for such a complex relationship.
- CThe model fails to improve meaningfully on the benchmark model.
- DThe model's adjusted R2 is too low for the real estate industry.
How the community answered
(35 responses)- A6% (2)
- B14% (5)
- C54% (19)
- D26% (9)
Explanation
Although the new model's RMSE is technically lower (995 vs. 1,000), the five-point improvement on holdout data is negligible in most real-estate contexts and unlikely to produce meaningful business value over the existing benchmark.
Topics
Community Discussion
No community discussion yet for this question.