From 8ea1e23298dff1180889294f326b896911efb31b Mon Sep 17 00:00:00 2001 From: Chris Russell Date: Mon, 19 Aug 2024 18:13:26 +0100 Subject: [PATCH] link to paper --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index b8f7518..316e846 100644 --- a/README.md +++ b/README.md @@ -4,7 +4,7 @@ OxonFair is an expressive toolkit designed to enforce a wide-range of fairness d The toolkit is designed to overcome a range of shortcomings in existing fairness toolkits for high-capacity models that overfit to the training data. It is designed and works for computer vision and NLP problems alongside tabular data. -Check out the colab demo [here](https://colab.research.google.com/drive/1CfcS3AX7M2MO1wW33wU1LDiY5DwtyyxH?usp=sharing). +Check out the colab demo [here](https://colab.research.google.com/drive/1CfcS3AX7M2MO1wW33wU1LDiY5DwtyyxH?usp=sharing) or read the [preprint](https://arxiv.org/abs/2407.13710). For low-capacity models (e.g., logistic regression over a small number of variables, and decision-trees of limited depth), we recommend [fairlearn](https://github.com/fairlearn/fairlearn). @@ -20,7 +20,7 @@ In the terminal type: pip install 'oxonfair[full]' -This will download and install enough code to run any notebooks except those comparing with fairlearn. This includes autogluon, pytorch, and XGBoost. If this is too many dependancies, try a minimal install. +This will download and install enough code to run any notebooks except those comparing with fairlearn. This includes autogluon, pytorch, and XGBoost. If this is too many dependencies, try a minimal install. ### Minimal install