EasySI: Easy 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://EasySI.github.io/

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

Implemented Features

EasySI 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 EasySI

Post installation check

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

import si

Note that for easier access the module is named si instead of EasySI.

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/.