polaris-liang / PIPC

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PIPC

Data Description: “ElectricityLoadDiagrams” in UCI, containing 370 customers with 140256 attributes, each of which gives the electricity consumption value every 15 minutes. As the attributes are too much, we accomplish dimension reduction such that each item has only four attributes.

data.txt

Put the following files in the same directory:

mvhe.py
kmeans.py
kmeansvhe.py
data.txt

We set K = 5, grouping 370 customers into five clusters.

Run the standard k-means clustering

python kmeans.py

The plaintext result is saved as

result.txt

Run the privacy-preserving k-means clustering

python kmeansvhe.py

The ciphertext result is saved as

vhe_result.txt

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