Clehrity
Features
EHR deconfounding via:
- Statistical tests of discontinuity / non-monotoncities
- Integration with LLMs to find surprising / counter-causal effects
Requirements
- Python >=3.9
Installation
You can install Clehrity via pip from PyPI:
$ pip install clehrity
Usage
Please see the Command-line Reference for details.
Contributing
Contributions are very welcome. To learn more, see the Contributor Guide.
License
Distributed under the terms of the MIT license, Clehrity is free and open source software.
Issues
If you encounter any problems, please file an issue along with a detailed description.
Credits
This project was generated from @cjolowicz's Hypermodern Python Cookiecutter template.
1 maintainer
Metadata
1 maintainer
Release files for clehrity 0.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| clehrity-0.0.1.tar.gz | 4.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| clehrity-0.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 9.2 kB
Release files / clehrity-0.0.1.tar.gz
| Download URL | clehrity-0.0.1.tar.gz |
|---|---|
| Size | 4.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.11.6
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Release files / clehrity-0.0.1-py3-none-any.whl
| Download URL | clehrity-0.0.1-py3-none-any.whl |
|---|---|
| Size | 4.9 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.11.6
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