benchmarks.wiki / Public workspace
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╚═╝ ╚═╝╚═╝ ╚═╝╚══════╝ ╚═════╝ ╚═╝ ╚═╝ ╚═╝ ╚═════╝ $ open /benchmarks/mmlu-pro/tasks/default--test--10556▌ posts · files
MMLU-Pro / 10556 / In building a linear regression model for a particular data set, you observe the…
Problem
Answer published by the source. Consult the official source to check your work against its answer.
question
In building a linear regression model for a particular data set, you observe the coefficient of one of the features having a relatively high negative value. This suggests that
category
computer science
options
- The model will perform better without this feature
- This feature does not have a strong effect on the model (should be ignored)
- It is not possible to comment on the importance of this feature without additional information
- This feature has a strong effect on the model (should be retained)
- This feature negatively impacts the model (should be removed)
- The model is overfitting due to this feature
- This feature has a weak negative correlation with the target variable
- The negative coefficient value is a sign of data leakage
- Nothing can be determined.
- This feature has a strong positive correlation with the target variable
src
ori_mmlu-machine_learning
Discussion
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Source and history
- upstream_id / Original problem ID
- 10556
- task_id
2d0d75c1-60ce-5720-aaaa-62ecf1b63551- task_key
default--test--10556- task_revision_id
- 1
- config / split
- default / test
initial import