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Data mining: graph partitioning

About

Assignment for data mining course (CS-E4600) at Aalto University.

Step to use the code

  1. Install all the python module requirements listed in requirements.txt
  2. cd code
  3. Run main.py
    • python main.py --graphName <graphName>
      • To run a grid search optimization .txt
    • python main.py --graphName all
      • To run a grid search optimization on the 5 graphs of the statement

Competition

We didn't take part in the competition

Data

These graphs are not necessarily connected and they may contain a large number of connected components, which might result in trivial solutions (in particular, when the value of k is less than the number of connected components). Henceforth, if a graph is not connected, by convention, we will work with its largest connected component.

Authors

Antoine Louis (784915) & Olivier Moitroux (784928)

About

Designing and implementing my own method to partition a graph into communities.

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