Este Scikit Learn sigur?
Scikit Learn — Nerq Trust Score 88.0/100 (Nota A). Pe baza analizei a 2 dimensiuni de încredere, este considerat sigur pentru utilizare. Ultima actualizare: 2026-04-05.
Da, Scikit Learn este sigur de utilizat. Scikit Learn este un Python package with a Nerq Trust Score of 88.0/100 (A), based on 3 independent data dimensions. It is recommended for production use. Security: 90/100. Popularity: 100/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-04-05. Date citibile de mașină (JSON).
Este Scikit Learn sigur?
YES — Scikit Learn has a Nerq Trust Score of 88.0/100 (A). It meets Nerq's trust threshold with strong signals across security, maintenance, and community adoption. Recommended for production use — review the full report below for specific considerations.
Care este scorul de încredere al Scikit Learn?
Scikit Learn are un Nerq Trust Score de 88.0/100 cu nota A. Acest scor se bazează pe 2 dimensiuni măsurate independent, inclusiv securitate, întreținere și adopție comunitară.
Care sunt principalele constatări de securitate pentru Scikit Learn?
Cel mai puternic semnal al Scikit Learn este popularitate la 100/100. Nu au fost detectate vulnerabilități cunoscute. It meets the Nerq Verified threshold of 70+.
Ce este Scikit Learn și cine îl întreține?
| Autor | Unknown |
| Categorie | pypi |
| Sursă | N/A |
Pypi similare după Scor de Încredere
Safety Guide: Scikit Learn
What is Scikit Learn?
Scikit Learn is a Python package — A set of python modules for machine learning and data mining.
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=scikit-learn
Key Safety Concerns for Python packages
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Trust Assessment
Scikit Learn has a Nerq Trust Score of 76/100 (B+) and meets Nerq trust threshold. This score is based on automated analysis of security, maintenance, community, and quality signals.
Key Takeaways
- Scikit Learn has a Trust Score of 76/100 (B+).
- Recommended for use — passes trust threshold.
- Always verify independently using the Nerq API.
Analiză detaliată a scorului
| Dimension | Score |
|---|---|
| Security | 90/100 |
| Privacy | 80/100 |
| Reliability | 90/100 |
| Transparency | 50/100 |
| Maintenance | 60/100 |
Based on 5 dimensions. Data from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard.
Ce date colectează Scikit Learn?
Scikit Learn is a Python package maintained by Unknown. It receives approximately 45,807,671 weekly downloads.
As a development package, Scikit Learn does not directly collect end-user personal data. However, applications built with it may collect data depending on implementation. Privacy score: 80/100.
Review the package's dependencies for potential supply chain risks. Run your package manager's audit command regularly.
Analiză completă: Raport de confidențialitate Scikit Learn · Privacy review
Este Scikit Learn sigur?
Security score: 90/100. Scikit Learn has 0 known vulnerabilities (CVEs) in the National Vulnerability Database. This is a clean record.
License information not available. Open-source packages allow independent security review of the source code.
Run your package manager's audit command (`npm audit`, `pip audit`, `cargo audit`) to check for known vulnerabilities in your dependency tree.
Analiză completă: Raport de securitate Scikit Learn
Cum am calculat acest scor
Scikit Learn's trust score of 88.0/100 (A) is computed from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. The score reflects 5 independent dimensions: security (90/100), privacy (80/100), reliability (90/100), transparency (50/100), maintenance (60/100). Each dimension is weighted equally to produce the composite trust score.
Nerq analyzes over 7.5 million entities across 26 registries using the same methodology, enabling direct cross-entity comparison. Scores are updated continuously as new data becomes available.
This page was last reviewed on April 05, 2026. Data version: 1.0.
Full methodology documentation · Machine-readable data (JSON API)
Întrebări frecvente
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Disclaimer: Scorurile de încredere Nerq sunt evaluări automatizate bazate pe semnale disponibile public. Nu sunt recomandări sau garanții. Efectuați întotdeauna propria verificare.