OpenSI: Open-source Selective Inference

This open source Python library provides APIs for selective inference for problems in machine learning such as feature selection, anomaly detection and domain adaptation.

Website and documentation: https://OpenSI.github.io/

Source code (MIT): https://github.com/OpenSI/OpenSI

Implemented Features

OpenSI have provide selective inference support for methods:

• Feature Selection:
  • Lasso Feature Selection
  • Sequential Feature Selection
• Domain Adaptation:
  • Optimal Transport-based Domain Adaptation

Installation

The library has only been tested on Windows with Python 3.10. It requires some of the following modules:

• numpy (=2.2.6)
• mpmath (=1.3.0)
• POT (==0.9.5)
• scikit-learn (==1.7.1)
• scipy (==1.15.3)

Note: Other versions of Python and dependencies shall be tested in the future.

Pip Installation

You can install the toolbox through PyPI with:

pip install OpenSI

Post installation check

After a correct installation, you should be able to import the module without errors:

import opensi

Examples and Notebooks

The examples folder contain several examples and use case for the library. The full documentation with examples and output is available on https://PythonSI.github.io/.