imbalanced-learn
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Overview
HEALTH SCORE
Fair
61out of 100
Security posture drags the score down. Maintainer coverage and development cadence help keep it from falling further.
LIFECYCLE
Active
Consistent commits, responsive maintainers, regular releases, and healthy issue triage.
Health breakdown
Fair(61/100)
Maintainer availability, known risks and supply chain posture, and whether the project is actively developed or appropriately stable.
Maintainer responsiveness
Median response time is 5 days.
Bus factor
4 active maintainers currently have merge rights.
Organization Diversity
Contributors span 30 organizations.
Project Achievements
Leaderboards
About
A Python package that provides tools and algorithms for handling imbalanced datasets in machine learning, offering various resampling techniques to address class imbalance problems
First commit
Software value
$816K
Tags
data-analysis
data-science
machine-learning
python
statistics
License(s)
MIT
Data sources
Git
GitHub