cvxreg is a Python package for machine learning with convex regression models built on CVXPY.
The core aims of this package are:
- make convex regression models "easy to call" from Python,
- interface with
CVXPY, - focus on a "machine learning" perspective, i.e.: predictive task, hyper-parameters should be obtained by a data-driven method such as cross-validation.
Installation
The cvxreg package is now available on PyPI and the latest development version can be installed from the GitHub repository ConvexRegression. Please feel free to download and test it. We welcome any bug reports and feedback.
PyPI
pip install cvxreg
1 maintainer
Release files for cvxreg 0.2.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| cvxreg-0.2.2.tar.gz | 28.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| cvxreg-0.2.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 60.3 kB
Release files / cvxreg-0.2.2.tar.gz
| Download URL | cvxreg-0.2.2.tar.gz |
|---|---|
| Size | 28.8 kB |
| Tags | Source |
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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/6.2.0 CPython/3.9.25
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Release files / cvxreg-0.2.2-py3-none-any.whl
| Download URL | cvxreg-0.2.2-py3-none-any.whl |
|---|---|
| Size | 31.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-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/6.2.0 CPython/3.9.25
|
