Name | adelie JSON |
Version |
1.1.51
JSON |
| download |
home_page | None |
Summary | A fast, flexible package for group elastic net. |
upload_time | 2024-11-27 06:06:50 |
maintainer | James Yang |
docs_url | None |
author | James Yang |
requires_python | >=3.9 |
license | MIT License Copyright (c) 2023 James Yang Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
keywords |
group lasso
group elastic net
lasso
elastic net
|
VCS |
 |
bugtrack_url |
|
requirements |
No requirements were recorded.
|
Travis-CI |
No Travis.
|
coveralls test coverage |
No coveralls.
|
<h1 align="center">
<img src="https://raw.githubusercontent.com/JamesYang007/adelie/main/docs/logos/adelie-penguin.svg" width="500">
</h1><br>

[](https://pepy.tech/project/adelie)
[](https://pepy.tech/project/adelie)



Adelie is a fast and flexible Python package for solving
lasso, elastic net, group lasso, and group elastic net problems.
- **Installation**: [https://jamesyang007.github.io/adelie/notebooks/installation.html](https://jamesyang007.github.io/adelie/notebooks/installation.html)
- **Documentation**: [https://jamesyang007.github.io/adelie](https://jamesyang007.github.io/adelie/)
- **Source code**: [https://github.com/JamesYang007/adelie](https://github.com/JamesYang007/adelie)
- **Issue Tracker**: [https://github.com/JamesYang007/adelie/issues](https://github.com/JamesYang007/adelie/issues)
It offers a general purpose group elastic net solver,
a wide range of matrix classes that can exploit special structure to allow large-scale inputs,
and an assortment of generalized linear model (GLM) classes for fitting various types of data.
These matrix and GLM classes can be extended by the user for added flexibility.
Many inner routines such as matrix-vector products
and gradient, hessian, and loss of GLM functions have been heavily optimized and parallelized.
Algorithmic optimizations such as the pivot rule for screening variables
and the proximal Newton method have been carefully tuned for convergence and numerical stability.
Raw data
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