opendv 0.0.1

An Open-Source Framework for Shapley-based value intened intended for data valuation.

An Open-Source Framework for Shapley-based value intened intended for data valuation.

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Overview • Installation • How To Use

What's New?

TBD $\text{\color{red}{!in progress}}$

Overview

Shapley-based values are prevalent data valuation approaches, which are attractive for its fair properties (axioms).

The approaches are planned to support including Shapley-based values and some other famous values for data valuation.

Shapley-based values:

• Shapley value
• Beta Shapley value
• KNN Shapley value
• Asymmetric Shapley value
• Robust Shapley value
• Cosine gradient Shapley value
• CS-Shapley value
• Banzhaf value
• Volumn-based Shapley value

Others:

• LOO
• DVRL
• Data-OOB

What Can You Do via OpenDV?

• Use the implementations of current Shapley-based values.* We have implemented various of Shapley-based values and corresponding SOTA computation techniques. You can easily call and understand these methods.
• Design your own data valuation work. With the extensibility of OpenDV, you can quickly practice your data valuation ideas.

Installation

Note: Please use Python 3.10+ for OpenDV

Using Pip

Our repo is tested on Python 3.10+, install OpenDV using pip as follows:

pip install opendv

To play with the latest features, you can also install OpenDV from the source.

Using Git

Clone the repository from github:

git clone https://github.com/ZJU-DIVER/OpenDV.git
cd opendv
pip install -r requirements.txt
python setup.py install

Modify the code

python setup.py develop

Use OpenDV

TBD

Base Concepts

TBD