From 3fdcb288f4765084f5ac291a5b3dc95a0b50871a Mon Sep 17 00:00:00 2001 From: joaopfonseca Date: Tue, 20 Feb 2024 14:24:17 +0000 Subject: [PATCH] DOC add more information + fix incorrect info (#13) --- README.md | 15 ++++++++++++++- 1 file changed, 14 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index e323b07..9bf96de 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,7 @@ # ShaRP +[![Documentation](https://github.com/DataResponsibly/ShaRP/actions/workflows/deploy-docs.yml/badge.svg)](https://dataresponsibly.github.io/ShaRP/) + ``ShaRP`` is an open source library with the implementation of the ShaRP algorithm (Shapley for Rankings and Preferences), a framework that can be used to explain the contributions of features to different aspects of a ranked @@ -18,7 +20,7 @@ Some functions require Matplotlib (>= 2.2.3) for plotting. ### User Installation -The easiest way to install ml-research is using ``pip`` : +The easiest way to install ``sharp`` is using ``pip`` : pip install -U xai-sharp @@ -45,3 +47,14 @@ project with minimal effort: # Install project requirements and the research package. Dependecy group # "all" will also install the dependency groups shown below. pip install .[optional,tests,docs] + +## Citing ShaRP + +If you use ``sharp`` in a scientific publication, we would appreciate citations to the following paper: + + @article{pliatsika2024sharp, + title={ShaRP: Explaining Rankings with Shapley Values}, + author={Pliatsika, Venetia and Fonseca, Joao and Wang, Tilun and Stoyanovich, Julia}, + journal={arXiv preprint arXiv:2401.16744}, + year={2024} + }