iiitl / iiitl/Logistic-Regression
Outcome balance and naive baseline check
Open
easy
exploration
good first issue
- Dominant language
- Jupyter Notebook
- Stars
- 0
- Forks
- 16
- PR merge metrics
- No merged PRs in 30d
Description
Compute Outcome class counts and percentages, then calculate majority-class baseline accuracy.
Explain in 4 points why accuracy alone is insufficient for this dataset.
Contributor guide
Research direction
Open the repository's notebook and locate the Outcome column and the existing model or dataset analysis. Add the class counts, percentages, majority-class baseline accuracy, and four points explaining why accuracy alone is insufficient; verify that the reported values match the dataset.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook
- Domain
- data, machine-learning
- Issue type
- Feature
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 55/100