Description:

opendv 0.0.1

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


Overview •
Installation •
How To Use


What's New?
TBD \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

License

For personal and professional use. You cannot resell or redistribute these repositories in their original state.

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