https://github.com/cyberagentailab/cenreg
https://github.com/cyberagentailab/cenreg
Last synced: 5 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/cyberagentailab/cenreg
- Owner: CyberAgentAILab
- License: apache-2.0
- Created: 2025-05-28T09:17:56.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-08-22T07:34:54.000Z (10 months ago)
- Last Synced: 2025-09-10T07:42:48.769Z (9 months ago)
- Language: Jupyter Notebook
- Size: 20.1 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
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README
# The `cenreg` Package
The Python package `cenreg` is repository for probabilistic forecasts such as quantile regression and distribution regression and for censored regression such as survival analysis and interval-censored data analysis.
## Getting Started
### Prerequisites
You first need to install `SurvSet` via pip
```
pip install SurvSet
```
Additionally, denpending on the models you want to use, you also need to install
+ LightGBM
+ PyTorch
### Installation
You can install `cenreg` via pip:
```
pip install cenreg
```
### Run Sample Code
You can find our sample codes in the `notebooks` directory.
### Documentation
Read the [documentation](https://cyberagentailab.github.io/cenreg/) to get started.
## Citation
[1] [H. Yanagisawa and S. Akiyama, Survival Analysis via Density Estimation, ICML 2025](https://icml.cc/virtual/2025/poster/43491) (Paper in [OpenReview](https://openreview.net/forum?id=z9SRjXPf8T))
```
@InProceedings{yanagisawa2025survival,
author = {Yanagisawa, Hiroki and Akiyama, Shunta},
booktitle = {Proceedings of ICML 2025},
title = {Survival Analysis via Density Estimation},
year = {2025},
}
```
[2] [H. Yanagisawa, Proper Scoring Rules for Survival Analysis, ICML 2023](https://proceedings.mlr.press/v202/yanagisawa23a/yanagisawa23a.pdf)
```
@InProceedings{yanagisawa2023proper,
author = {Yanagisawa, Hiroki},
booktitle = {Proceedings of ICML 2023},
title = {Proper Scoring Rules for Survival Analysis},
year = {2023},
}
```