Post-modeling: bias statistics and plots
Open
postmodeling
- Dominant language
- Jupyter Notebook
- Stars
- 201
- Forks
- 62
- PR merge metrics
- No merged PRs in 30d
Description
This should include analyses per model across thresholds, per model and threshold across time, and per time and threshold across models.
Contributor guide
Research direction
The issue names no files, tests, or entry points. Start by locating the post-modeling analysis code and how models, thresholds, and time periods are represented; then determine how the requested statistics and plots should cover each combination. Done means analyses exist for all three perspectives described in the issue.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook, python
- Domain
- data-visualization, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100