This release looks at the role of joint feature importance for explainability in instances where features may be highly correlated when providing an output. Specifically, the method operates by regrouping the correlated features and then looking at the group-level impact of imputation. Doing so allows us to consider the impact of a joint permutation of the correlated features.
Some examples are available in examples
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 groufiTo 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 --versionThen, you can clone the git repository:
git clone git@github.com:BorealisAI/group-feature-importance.gitThen, 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 condaIt automatically creates a conda virtual environment. When the virtual environment is created, you can activate it with the following command:
conda activate groufiThis 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 installThis 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 testThis repository is released under the Attribution-NonCommercial-ShareAlike 4.0 International license as found in the LICENSE file.