What is causalml?
causalml is a pypi that Python Package for Uplift Modeling and Causal Inference with Machine Learning Algorithms. It has a Nerq Trust Score of 64/100 (C+). 0 GitHub stars. Published by Huigang Chen, Totte Harinen, Jeong-Yoon Lee, Jing Pan, Mike Yung, Zhenyu Zhao. Last analyzed June 2026.
Why This Score
- ⚠️ Security: 0/100 — Some security concerns
- ⚠️ Maintenance: 0/100 — Maintenance activity is low
- ⚠️ Community: 0 stars, 0 downloads — Growing community
- ⚠️ Transparency: License: Not specified — No license specified
Trust & Safety Overview
What causalml Does
causalml is a pypi in the pypi category. Python Package for Uplift Modeling and Causal Inference with Machine Learning Algorithms. It is published by Huigang Chen, Totte Harinen, Jeong-Yoon Lee, Jing Pan, Mike Yung, Zhenyu Zhao and has no specified license. With 0 GitHub stars and 0 downloads, it has a small community of users and contributors.
Who Should Use causalml
causalml is suitable for evaluation and non-critical use. Review the trust score breakdown before using in production.
Details
| Author | Huigang Chen, Totte Harinen, Jeong-Yoon Lee, Jing Pan, Mike Yung, Zhenyu Zhao |
|---|---|
| Category | pypi |
| License | Not specified |
| Type | pypi |
| Source | View on GitHub |
| Security Score | 0/100 |
| Activity Score | 0/100 |
How to Get Started
Check the trust score before installing:
curl nerq.ai/v1/preflight?target=causalml
Setup guide · Full safety report · Production review · Is it safe?
Frequently Asked Questions
Last updated June 2026. Trust scores based on automated analysis of public data.