Python Package of Simplex-based Multinomial Logistic Regression
Project description
SMLR Project
Introduction
This is a project of SMLR (Simplex-based Multinomial Logistic Regression) + Penalty.
Starter Guidance
By pip
To create a virtual env in your device, use:
python3 -m venv .venv
Then use pip to install:
pip install -e .
By uv
If you have uv as your venv tool for Python, just type:
uv sync
run test_smlr.py
python3 test_smlr.py
References
[1] S. Fu, P. Chen, Y. Liu, and Z. Ye, “Simplex-based Multinomial Logistic Regression with Diverging Numbers of Categories and Covariates,” STAT SINICA, 2024, doi: 10.5705/ss.202021.0082.
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file smlr_learn-0.1.0.tar.gz.
File metadata
- Download URL: smlr_learn-0.1.0.tar.gz
- Upload date:
- Size: 8.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: uv/0.9.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
9985014426f878b43b891d0cffe77b779a74098178fda9f669d175bf08804b64
|
|
| MD5 |
14c1835d60edd1f72a0e889ba4ad50a6
|
|
| BLAKE2b-256 |
60f70ae53613f98b177cac89d4aeb2a664f244f017e56d93a9dcfc357657e9a6
|
File details
Details for the file smlr_learn-0.1.0-py3-none-any.whl.
File metadata
- Download URL: smlr_learn-0.1.0-py3-none-any.whl
- Upload date:
- Size: 8.6 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: uv/0.9.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
805dd5f3de7d646ce381fa7d254c70b2636c1ef24dc2995984616509adcfec4c
|
|
| MD5 |
06ff053a4100f95bdc91133e185b5c98
|
|
| BLAKE2b-256 |
873b2d434bbea43481f4fdee248584eef0681b7eb59d6542e4634d37dc8e9150
|
