A small library to compute group feature importance
Project description
Group feature importance
This repo contains the implementation to compute feature importance of correlated features.
Examples
Some examples are available in examples
Installation
Installing with pip
This repository is tested on Python 3.9, and Linux systems. It is recommended to install in a virtual environment to keep your system in order. The following command installs the latest version of the library:
pip install groufi
Installing from source
To install groufi
from source, you can follow the steps below. First, you will need to
install poetry
. poetry
is used to manage and install the dependencies.
If poetry
is already installed on your machine, you can skip this step. There are several ways to install poetry
so
you can use the one that you prefer. You can check the poetry
installation by running the following command:
poetry --version
Then, you can clone the git repository:
git clone git@github.com:BorealisAI/group-feature-importance.git
Then, it is recommended to create a Python 3.8+ virtual environment. This step is optional so you can skip it. To create a virtual environment, you can use the following command:
make conda
It automatically creates a conda virtual environment. When the virtual environment is created, you can activate it with the following command:
conda activate groufi
This example uses conda
to create a virtual environment, but you can use other tools or configurations. Then, you
should install the required package to use groufi
with the following command:
make install
This command will install all the required packages. You can also use this command to update the required packages. This command will check if there is a more recent package available and will install it. Finally, you can test the installation with the following command:
make test
License
This repository is released under the Attribution-NonCommercial-ShareAlike 4.0 International license as found in the LICENSE file.
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