This repo contains experimental code that is used to understand how the popular k-means algorithm could be used in identifying collusion in a quadratic funding round.
- When a ballot is at the same distance of two centroids, the first one is the one they are assigned to.
Coefficients can be calculated in two ways:
$1- clusterSize/totalVoters$ $clusterSize/totalVoters$
Funds allocation can be calculated in two ways:
- squaring before applying the coefficient
- squaring after applying the coefficient
- clone the repo:
git@github.com:ctrlc03/qfi-kmeans.git - install the dependencies:
yarn - run tests for the typescript implementation:
yarn test:tsandyarn test:class - run tests for the circom implementation:
yarn test:circom - to run all possible combinations of calculations and the elbow method (which can be used to identify the optimal value for k) use:
./plotting.sh(needs execute permissions first)
Please note that this stores a very large amount of files on disk (json and png files)
- to plot the data of a single run of the algorithm you can use the Python scripts inside src/plotting:
python3 src/plotting/x.py $k - Fetch GitCoin round data (you need to fill the .env file first - copy .env.template):
yarn gitcoinyarn parse:gitcoin - Run k-means on Gitcoin round data
yarn start:gitcoin