Is Imbalanced Learn Safe?
Imbalanced Learn — Nerq Trust Score 68.2/100 (B- grade). Score based on 2 independent trust signals. Last analyzed: 2026-07-22
Imbalanced Learn is a Python package with a Nerq Trust Score of 68.2/100 (B-), based on 3 independent data dimensions. Last analyzed: 2026-07-22 Security: 90/100. Popularity: 100/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-07-22. Machine-readable data (JSON).
Is Imbalanced Learn safe?
Trust Score Breakdown — Imbalanced Learn has a Nerq Trust Score of 68.2/100 (B-). Measured across 2 independent trust signals (as of 2026-07-22).
What is Imbalanced Learn's trust score?
Imbalanced Learn has a Nerq Trust Score of 68.2/100, earning a B- grade. This score is based on 2 independently measured dimensions including security, maintenance, and community adoption.
What are the key security findings for Imbalanced Learn?
Imbalanced Learn's strongest signal is popularity at 100/100. No known vulnerabilities have been detected.
What is Imbalanced Learn and who maintains it?
| Author | Unknown |
| Category | Python Packages |
| Source | N/A |
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Safety Guide: Imbalanced Learn
What is Imbalanced Learn?
Imbalanced Learn is a Python package — Toolbox for imbalanced dataset in machine learning.
How to Verify Safety
Run pip audit or safety check. Review on PyPI for download stats.
You can also check the trust score via API: GET /v1/preflight?target=imbalanced-learn
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Measured Signals
Imbalanced Learn has a Nerq Trust Score of 68/100 (B-). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Key Takeaways
- Imbalanced Learn has a Trust Score of 68/100 (B-).
- The score is a measured composite — it is not a suitability judgment. Evaluate the individual signals against your own requirements.
- Query the current measured values via the Nerq API.
Frequently Asked Questions
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Disclaimer: Nerq trust scores are automated measurements based on publicly available signals. They are not endorsements, verdicts, or guarantees of suitability. Always evaluate the signals against your own requirements.