Metadata-Version: 2.4
Name: cort-si
Version: 0.0.1
Summary: A framework to conduct selective inference for Co-Regularization Enhances Knowledge Transfer (CoRT)
Author-email: Pham Bach Hiep <bachhiepforwork@gmail.com>, Nguyen Ngoc Nho <ngocnho2605n@gmail.com>, Nguyen Vo Le Duy <duyvnl@uit.edu.vn>
License-Expression: MIT
Project-URL: Homepage, https://github.com/Park-Hip/Selective_Inference_For_CoRT
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: scikit-learn
Requires-Dist: numpy
Requires-Dist: mpmath
Dynamic: license-file

# CoRT-SI: Selective Inference For Co-Regularization Transfer (CoRT)

**CoRT-SI** is a Python package designed for conducting valid statistical inference for CoRT. It implements selective inference methods to control the false positive rate (FPR) while maximizing the true positive rate (TPR) in feature selection after transfer learning.

## Requirements & Installation

This package has the following requirements:

* `numpy`
* `mpmath`          
* `scikit-learn`


This package can be installed using pip:

```bash
pip install cort-si
