iiitl / iiitl/Logistic-Regression
Feature distribution by Outcome class
Open
exploration
medium
- Dominant language
- Jupyter Notebook
- Stars
- 0
- Forks
- 16
- PR merge metrics
- No merged PRs in 30d
Description
Compare Outcome 0 vs Outcome 1 distributions for at least 5 important features using clear plots.
Summarize which features show strongest class separation and where overlap is high.
Contributor guide
Research direction
Start by locating the project notebook and reviewing the Outcome column and existing feature analysis. Create clear distribution plots for at least five important features, compare Outcome 0 with Outcome 1, and summarize the strongest class separation and areas of overlap.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook
- Domain
- data-visualization, machine-learning
- Issue type
- Feature
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 58/100